A complete list of papers about adversarial examples

It appears that the List of All Adversarial Example Papers has been experiencing crashes over the past few days. In the absence of this valuable resource, staying up-to-date with the latest research papers in this field has become challenging. Consequently, I created a repository aimed at aggregating and maintaining the most current papers in this domain. While this repository may not encompass every paper, I did try. If you find any papers we have missed, just drop me an email. We have included the data from List of All Adversarial Example Papers till 2023-09-01. We also provide a list of papers about transfer-based attacks here.

2024-08-08

• Towards Resilient and Efficient LLMs: A Comparative Study of Efficiency, Performance, and Adversarial Robustness

  Xiaojing Fan, Chunliang Tao

• Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit

  Duanyi Yao, Songze Li, Ye Xue, Jin Liu

• FDI: Attack Neural Code Generation Systems through User Feedback Channel

  Zhensu Sun, Xiaoning Du, Xiapu Luo, Fu Song, David Lo, Li Li

2024-08-07

• EnJa: Ensemble Jailbreak on Large Language Models

  Jiahao Zhang, Zilong Wang, Ruofan Wang, Xingjun Ma, Yu-Gang Jiang

• LaFA: Latent Feature Attacks on Non-negative Matrix Factorization

  Minh Vu, Ben Nebgen, Erik Skau, Geigh Zollicoffer, Juan Castorena, Kim Rasmussen, Boian Alexandrov, Manish Bhattarai

• TALE: Training-free Cross-domain Image Composition via Adaptive Latent Manipulation and Energy-guided Optimization

  Kien T. Pham, Jingye Chen, Qifeng Chen

• Enhancing Output Diversity Improves Conjugate Gradient-based Adversarial Attacks

  Keiichiro Yamamura, Issa Oe, Hiroki Ishikura, Katsuki Fujisawa

• PushPull-Net: Inhibition-driven ResNet robust to image corruptions

  Guru Swaroop Bennabhaktula, Enrique Alegre, Nicola Strisciuglio, George Azzopardi

• Exploring RAG-based Vulnerability Augmentation with LLMs

  Seyed Shayan Daneshvar, Yu Nong, Xu Yang, Shaowei Wang, Haipeng Cai

2024-08-05

• RCDM: Enabling Robustness for Conditional Diffusion Model

  Weifeng Xu, Xiang Zhu, Xiaoyong Li

• Mitigating Malicious Attacks in Federated Learning via Confidence-aware Defense

  Qilei Li, Ahmed M. Abdelmoniem

• Sample-agnostic Adversarial Perturbation for Vision-Language Pre-training Models

  Haonan Zheng, Wen Jiang, Xinyang Deng, Wenrui Li

2024-08-02

• Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition

  Róisín Luo, James McDermott, Colm O'Riordan

• Mission Impossible: A Statistical Perspective on Jailbreaking LLMs

  Jingtong Su, Julia Kempe, Karen Ullrich

• Hallu-PI: Evaluating Hallucination in Multi-modal Large Language Models within Perturbed Inputs

  Peng Ding, Jingyu Wu, Jun Kuang, Dan Ma, Xuezhi Cao, Xunliang Cai, Shi Chen, Jiajun Chen, Shujian Huang

• Assessing Robustness of Machine Learning Models using Covariate Perturbations

  Arun Prakash R, Anwesha Bhattacharyya, Joel Vaughan, Vijayan N. Nair

• EmoBack: Backdoor Attacks Against Speaker Identification Using Emotional Prosody

  Coen Schoof, Stefanos Koffas, Mauro Conti, Stjepan Picek

2024-08-01

• Contrastive Graph Representation Learning with Adversarial Cross-view Reconstruction and Information Bottleneck

  Yuntao Shou, Haozhi Lan, Xiangyong Cao

• ADBM: Adversarial diffusion bridge model for reliable adversarial purification

  Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yining Liu, Yingzhe He, Jie Shi, Xiaolin Hu

• OTAD: An Optimal Transport-Induced Robust Model for Agnostic Adversarial Attack

  Kuo Gai, Sicong Wang, Shihua Zhang

• CERT-ED: Certifiably Robust Text Classification for Edit Distance

  Zhuoqun Huang, Neil G Marchant, Olga Ohrimenko, Benjamin I. P. Rubinstein

• Autonomous LLM-Enhanced Adversarial Attack for Text-to-Motion

  Honglei Miao, Fan Ma, Ruijie Quan, Kun Zhan, Yi Yang

• Revocable Backdoor for Deep Model Trading

  Yiran Xu, Nan Zhong, Zhenxing Qian, Xinpeng Zhang

• Adversarial Text Rewriting for Text-aware Recommender Systems

  Sejoon Oh, Gaurav Verma, Srijan Kumar

• Benchmarking Attacks on Learning with Errors

  Emily Wenger, Eshika Saxena, Mohamed Malhou, Ellie Thieu, Kristin Lauter

2024-07-31

• Measuring What Matters: Intrinsic Distance Preservation as a Robust Metric for Embedding Quality

  Steven N. Hart, Thomas E. Tavolara

• Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?

  Richard Ren, Steven Basart, Adam Khoja, Alice Gatti, Long Phan, Xuwang Yin, Mantas Mazeika, Alexander Pan, Gabriel Mukobi, Ryan H. Kim, Stephen Fitz, Dan Hendrycks

• Defending Jailbreak Attack in VLMs via Cross-modality Information Detector

  Yue Xu, Xiuyuan Qi, Zhan Qin, Wenjie Wang

• Benchmarking AIGC Video Quality Assessment: A Dataset and Unified Model

  Zhichao Zhang, Xinyue Li, Wei Sun, Jun Jia, Xiongkuo Min, Zicheng Zhang, Chunyi Li, Zijian Chen, Puyi Wang, Zhongpeng Ji, Fengyu Sun, Shangling Jui, Guangtao Zhai

• Conditioned Prompt-Optimization for Continual Deepfake Detection

  Francesco Laiti, Benedetta Liberatori, Thomas De Min, Elisa Ricci

• Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMs

  Shi Liu, Kecheng Zheng, Wei Chen

• Diff-Cleanse: Identifying and Mitigating Backdoor Attacks in Diffusion Models

  Jiang Hao, Xiao Jin, Hu Xiaoguang, Chen Tianyou

• Resilience and Security of Deep Neural Networks Against Intentional and Unintentional Perturbations: Survey and Research Challenges

  Sazzad Sayyed, Milin Zhang, Shahriar Rifat, Ananthram Swami, Michael De Lucia, Francesco Restuccia

2024-07-30

• FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks

  Hunmin Yang, Jongoh Jeong, Kuk-Jin Yoon

• Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks

  Hunmin Yang, Jongoh Jeong, Kuk-Jin Yoon

• PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning

  Muhammad Anwar Ma'sum, Mahardhika Pratama, Savitha Ramasamy, Lin Liu, Habibullah Habibullah, Ryszard Kowalczyk

• Vulnerabilities in AI-generated Image Detection: The Challenge of Adversarial Attacks

  Yunfeng Diao, Naixin Zhai, Changtao Miao, Xun Yang, Meng Wang

• Can LLMs be Fooled? Investigating Vulnerabilities in LLMs

  Sara Abdali, Jia He, CJ Barberan, Richard Anarfi

• Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification

  Boyang Zhang, Yicong Tan, Yun Shen, Ahmed Salem, Michael Backes, Savvas Zannettou, Yang Zhang

• DeepBaR: Fault Backdoor Attack on Deep Neural Network Layers

  C. A. Martínez-Mejía, J. Solano, J. Breier, D. Bucko, X. Hou

2024-07-29

• Can Editing LLMs Inject Harm?

  Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu

• Detecting and Understanding Vulnerabilities in Language Models via Mechanistic Interpretability

  Jorge García-Carrasco, Alejandro Maté, Juan Trujillo

• RSC-SNN: Exploring the Trade-off Between Adversarial Robustness and Accuracy in Spiking Neural Networks via Randomized Smoothing Coding

  Keming Wu, Man Yao, Yuhong Chou, Xuerui Qiu, Rui Yang, Bo Xu, Guoqi Li

• BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning

  Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu, Shaokui Wei, Danni Yuan, Mingli Zhu, Ruotong Wang, Li Liu, Chao Shen

• Practical and Robust Safety Guarantees for Advanced Counterfactual Learning to Rank

  Shashank Gupta, Harrie Oosterhuis, Maarten de Rijke

• Contrasting Deepfakes Diffusion via Contrastive Learning and Global-Local Similarities

  Lorenzo Baraldi, Federico Cocchi, Marcella Cornia, Lorenzo Baraldi, Alessandro Nicolosi, Rita Cucchiara

• From ML to LLM: Evaluating the Robustness of Phishing Webpage Detection Models against Adversarial Attacks

  Aditya Kulkarni, Vivek Balachandran, Dinil Mon Divakaran, Tamal Das

• Enhancing Adversarial Text Attacks on BERT Models with Projected Gradient Descent

  Hetvi Waghela, Jaydip Sen, Sneha Rakshit

2024-07-28

• Exploring the Adversarial Robustness of CLIP for AI-generated Image Detection

  Vincenzo De Rosa, Fabrizio Guillaro, Giovanni Poggi, Davide Cozzolino, Luisa Verdoliva

2024-07-27

• Towards Clean-Label Backdoor Attacks in the Physical World

  Thinh Dao, Cuong Chi Le, Khoa D Doan, Kok-Seng Wong

• EaTVul: ChatGPT-based Evasion Attack Against Software Vulnerability Detection

  Shigang Liu, Di Cao, Junae Kim, Tamas Abraham, Paul Montague, Seyit Camtepe, Jun Zhang, Yang Xiang

• Debiased Graph Poisoning Attack via Contrastive Surrogate Objective

  Kanghoon Yoon, Yeonjun In, Namkyeong Lee, Kibum Kim, Chanyoung Park

2024-07-26

• Adversarial Robustification via Text-to-Image Diffusion Models

  Daewon Choi, Jongheon Jeong, Huiwon Jang, Jinwoo Shin

• Robust VAEs via Generating Process of Noise Augmented Data

  Hiroo Irobe, Wataru Aoki, Kimihiro Yamazaki, Yuhui Zhang, Takumi Nakagawa, Hiroki Waida, Yuichiro Wada, Takafumi Kanamori

• Accuracy-Privacy Trade-off in the Mitigation of Membership Inference Attack in Federated Learning

  Sayyed Farid Ahamed, Soumya Banerjee, Sandip Roy, Devin Quinn, Marc Vucovich, Kevin Choi, Abdul Rahman, Alison Hu, Edward Bowen, Sachin Shetty

2024-07-25

• A Unified Understanding of Adversarial Vulnerability Regarding Unimodal Models and Vision-Language Pre-training Models

  Haonan Zheng, Xinyang Deng, Wen Jiang, Wenrui Li

• The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models

  Zihui Wu, Haichang Gao, Jianping He, Ping Wang

• Peak-Controlled Logits Poisoning Attack in Federated Distillation

  Yuhan Tang, Aoxu Zhang, Zhiyuan Wu, Bo Gao, Tian Wen, Yuwei Wang, Sheng Sun

• Is the Digital Forensics and Incident Response Pipeline Ready for Text-Based Threats in LLM Era?

  Avanti Bhandarkar, Ronald Wilson, Anushka Swarup, Mengdi Zhu, Damon Woodard

• Sparse vs Contiguous Adversarial Pixel Perturbations in Multimodal Models: An Empirical Analysis

  Cristian-Alexandru Botocan, Raphael Meier, Ljiljana Dolamic

• RIDA: A Robust Attack Framework on Incomplete Graphs

  Jianke Yu, Hanchen Wang, Chen Chen, Xiaoyang Wang, Wenjie Zhang, Ying Zhang

• Adversarial Robust Decision Transformer: Enhancing Robustness of RvS via Minimax Returns-to-go

  Xiaohang Tang, Afonso Marques, Parameswaran Kamalaruban, Ilija Bogunovic

2024-07-24

• Robust Deep Hawkes Process under Label Noise of Both Event and Occurrence

  Xiaoyu Tan, Bin Li, Xihe Qiu, Jingjing Huang, Yinghui Xu, Wei Chu

• How Good (Or Bad) Are LLMs at Detecting Misleading Visualizations?

  Leo Yu-Ho Lo, Huamin Qu

• Physical Adversarial Attack on Monocular Depth Estimation via Shape-Varying Patches

  Chenxing Zhao, Yang Li, Shihao Wu, Wenyi Tan, Shuangju Zhou, Quan Pan

• Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?

  Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang

• From Sands to Mansions: Enabling Automatic Full-Life-Cycle Cyberattack Construction with LLM

  Lingzhi Wang, Jiahui Wang, Kyle Jung, Kedar Thiagarajan, Emily Wei, Xiangmin Shen, Yan Chen, Zhenyuan Li

2024-07-23

• Figure it Out: Analyzing-based Jailbreak Attack on Large Language Models

  Shi Lin, Rongchang Li, Xun Wang, Changting Lin, Wenpeng Xing, Meng Han

• RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agent

  Huiyu Xu, Wenhui Zhang, Zhibo Wang, Feng Xiao, Rui Zheng, Yunhe Feng, Zhongjie Ba, Kui Ren

• Can Large Language Models Automatically Jailbreak GPT-4V?

  Yuanwei Wu, Yue Huang, Yixin Liu, Xiang Li, Pan Zhou, Lichao Sun

• Algebraic Adversarial Attacks on Integrated Gradients

  Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew

• STATE: A Robust ATE Estimator of Heavy-Tailed Metrics for Variance Reduction in Online Controlled Experiments

  Hao Zhou, Kun Sun, Shaoming Li, Yangfeng Fan, Guibin Jiang, Jiaqi Zheng, Tao Li

• Backdoor Attacks against Hybrid Classical-Quantum Neural Networks

  Ji Guo, Wenbo Jiang, Rui Zhang, Wenshu Fan, Jiachen Li, Guoming Lu

• Multimodal Unlearnable Examples: Protecting Data against Multimodal Contrastive Learning

  Xinwei Liu, Xiaojun Jia, Yuan Xun, Siyuan Liang, Xiaochun Cao

• Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory

  Xiaojin Zhang, Wei Chen

• S-E Pipeline: A Vision Transformer (ViT) based Resilient Classification Pipeline for Medical Imaging Against Adversarial Attacks

  Neha A S, Vivek Chaturvedi, Muhammad Shafique

2024-07-22

• ImPress: Securing DRAM Against Data-Disturbance Errors via Implicit Row-Press Mitigation

  Moinuddin Qureshi, Anish Saxena, Aamer Jaleel

2024-07-18

• DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving

  Yuxuan Tong, Xiwen Zhang, Rui Wang, Ruidong Wu, Junxian He

• Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning

  Vittorio Giammarino, James Queeney, Ioannis Ch. Paschalidis

• Cross-Task Attack: A Self-Supervision Generative Framework Based on Attention Shift

  Qingyuan Zeng, Yunpeng Gong, Min Jiang

• Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models

  Zhuo Chen, Jiawei Liu, Haotan Liu, Qikai Cheng, Fan Zhang, Wei Lu, Xiaozhong Liu

• Unveiling Structural Memorization: Structural Membership Inference Attack for Text-to-Image Diffusion Models

  Qiao Li, Xiaomeng Fu, Xi Wang, Jin Liu, Xingyu Gao, Jiao Dai, Jizhong Han

• PG-Attack: A Precision-Guided Adversarial Attack Framework Against Vision Foundation Models for Autonomous Driving

  Jiyuan Fu, Zhaoyu Chen, Kaixun Jiang, Haijing Guo, Shuyong Gao, Wenqiang Zhang

• Krait: A Backdoor Attack Against Graph Prompt Tuning

  Ying Song, Rita Singh, Balaji Palanisamy

• Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection

  Chunjing Xiao, Shikang Pang, Wenxin Tai, Yanlong Huang, Goce Trajcevski, Fan Zhou

• Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls

  Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi, Vamsi Potluru, Tucker Balch, Manuela Veloso

• BiasDPO: Mitigating Bias in Language Models through Direct Preference Optimization

  Ahmed Allam

• A Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion Attacks

  Yixiang Qiu, Hao Fang, Hongyao Yu, Bin Chen, MeiKang Qiu, Shu-Tao Xia

2024-07-17

• Turning Generative Models Degenerate: The Power of Data Poisoning Attacks

  Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Farhan Ahmed, Ling Cai, Nathalie Baracaldo

• Any Target Can be Offense: Adversarial Example Generation via Generalized Latent Infection

  Youheng Sun, Shengming Yuan, Xuanhan Wang, Lianli Gao, Jingkuan Song

• Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks

  Antoni Kowalczuk, Jan Dubiński, Atiyeh Ashari Ghomi, Yi Sui, George Stein, Jiapeng Wu, Jesse C. Cresswell, Franziska Boenisch, Adam Dziedzic

• LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models

  Kaichen Zhang, Bo Li, Peiyuan Zhang, Fanyi Pu, Joshua Adrian Cahyono, Kairui Hu, Shuai Liu, Yuanhan Zhang, Jingkang Yang, Chunyuan Li, Ziwei Liu

• Preventing Catastrophic Overfitting in Fast Adversarial Training: A Bi-level Optimization Perspective

  Zhaoxin Wang, Handing Wang, Cong Tian, Yaochu Jin

• Contrastive Adversarial Training for Unsupervised Domain Adaptation

  Jiahong Chen, Zhilin Zhang, Lucy Li, Behzad Shahrasbi, Arjun Mishra

• AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases

  Zhaorun Chen, Zhen Xiang, Chaowei Xiao, Dawn Song, Bo Li

• Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion

  Sanghyun Kim, Seohyeon Jung, Balhae Kim, Moonseok Choi, Jinwoo Shin, Juho Lee

• Direct Unlearning Optimization for Robust and Safe Text-to-Image Models

  Yong-Hyun Park, Sangdoo Yun, Jin-Hwa Kim, Junho Kim, Geonhui Jang, Yonghyun Jeong, Junghyo Jo, Gayoung Lee

2024-07-16

• EARN Fairness: Explaining, Asking, Reviewing and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders

  Lin Luo, Yuri Nakao, Mathieu Chollet, Hiroya Inakoshi, Simone Stumpf

• Feature Inference Attack on Shapley Values

  Xinjian Luo, Yangfan Jiang, Xiaokui Xiao

• AEMIM: Adversarial Examples Meet Masked Image Modeling

  Wenzhao Xiang, Chang Liu, Hang Su, Hongyang Yu

• Enhancing TinyML Security: Study of Adversarial Attack Transferability

  Parin Shah, Yuvaraj Govindarajulu, Pavan Kulkarni, Manojkumar Parmar

• Variational Randomized Smoothing for Sample-Wise Adversarial Robustness

  Ryo Hase, Ye Wang, Toshiaki Koike-Akino, Jing Liu, Kieran Parsons

• Does Refusal Training in LLMs Generalize to the Past Tense?

  Maksym Andriushchenko, Nicolas Flammarion

• Model Inversion Attacks Through Target-Specific Conditional Diffusion Models

  Ouxiang Li, Yanbin Hao, Zhicai Wang, Bin Zhu, Shuo Wang, Zaixi Zhang, Fuli Feng

• Cycle Contrastive Adversarial Learning for Unsupervised image Deraining

  Chen Zhao, Weiling Cai, ChengWei Hu, Zheng Yuan

• SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge

  Hao Ding, Tuxun Lu, Yuqian Zhang, Ruixing Liang, Hongchao Shu, Lalithkumar Seenivasan, Yonghao Long, Qi Dou, Cong Gao, Mathias Unberath

• IPA-NeRF: Illusory Poisoning Attack Against Neural Radiance Fields

  Wenxiang Jiang, Hanwei Zhang, Shuo Zhao, Zhongwen Guo, Hao Wang

• UNIT: Backdoor Mitigation via Automated Neural Distribution Tightening

  Siyuan Cheng, Guangyu Shen, Kaiyuan Zhang, Guanhong Tao, Shengwei An, Hanxi Guo, Shiqing Ma, Xiangyu Zhang

• Relaxing Graph Transformers for Adversarial Attacks

  Philipp Foth, Lukas Gosch, Simon Geisler, Leo Schwinn, Stephan Günnemann

• One-Shot Unlearning of Personal Identities

  Thomas De Min, Subhankar Roy, Massimiliano Mancini, Stéphane Lathuilière, Elisa Ricci

• Generalized Coverage for More Robust Low-Budget Active Learning

  Wonho Bae, Junhyug Noh, Danica J. Sutherland

2024-07-15

• Backdoor Attacks against Image-to-Image Networks

  Wenbo Jiang, Hongwei Li, Jiaming He, Rui Zhang, Guowen Xu, Tianwei Zhang, Rongxing Lu

• Learning to Unlearn for Robust Machine Unlearning

  Mark He Huang, Lin Geng Foo, Jun Liu

• Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks

  Quang H. Nguyen, Nguyen Ngoc-Hieu, The-Anh Ta, Thanh Nguyen-Tang, Hoang Thanh-Tung, Khoa D. Doan

• Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks

  Lukas Gosch, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar, Stephan Günnemann

2024-07-14

• Look Within, Why LLMs Hallucinate: A Causal Perspective

  He Li, Haoang Chi, Mingyu Liu, Wenjing Yang

• Augmented Neural Fine-Tuning for Efficient Backdoor Purification

  Nazmul Karim, Abdullah Al Arafat, Umar Khalid, Zhishan Guo, Nazanin Rahnavard

• CLIP-Guided Networks for Transferable Targeted Attacks

  Hao Fang, Jiawei Kong, Bin Chen, Tao Dai, Hao Wu, Shu-Tao Xia

• SENTINEL: Securing Indoor Localization against Adversarial Attacks with Capsule Neural Networks

  Danish Gufran, Pooja Anandathirtha, Sudeep Pasricha

• Towards Adversarially Robust Vision-Language Models: Insights from Design Choices and Prompt Formatting Techniques

  Rishika Bhagwatkar, Shravan Nayak, Reza Bayat, Alexis Roger, Daniel Z Kaplan, Pouya Bashivan, Irina Rish

• Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models

  Qingcheng Zeng, Mingyu Jin, Qinkai Yu, Zhenting Wang, Wenyue Hua, Zihao Zhou, Guangyan Sun, Yanda Meng, Shiqing Ma, Qifan Wang, Felix Juefei-Xu, Kaize Ding, Fan Yang, Ruixiang Tang, Yongfeng Zhang

2024-07-13

• Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning

  Shihua Sun, Shridatt Sugrim, Angelos Stavrou, Haining Wang

• SemiAdv: Query-Efficient Black-Box Adversarial Attack with Unlabeled Images

  Mingyuan Fan, Yang Liu, Cen Chen, Ximeng Liu

2024-07-12

• Towards More Trustworthy and Interpretable LLMs for Code through Syntax-Grounded Explanations

  David N. Palacio, Daniel Rodriguez-Cardenas, Alejandro Velasco, Dipin Khati, Kevin Moran, Denys Poshyvanyk

• Robustness of LLMs to Perturbations in Text

  Ayush Singh, Navpreet Singh, Shubham Vatsal

• Refusing Safe Prompts for Multi-modal Large Language Models

  Zedian Shao, Hongbin Liu, Yuepeng Hu, Neil Zhenqiang Gong

• Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training

  Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, Jiahao Xu, Tian Liang, Pinjia He, Zhaopeng Tu

• TAPI: Towards Target-Specific and Adversarial Prompt Injection against Code LLMs

  Yuchen Yang, Hongwei Yao, Bingrun Yang, Yiling He, Yiming Li, Tianwei Zhang, Zhan Qin, Kui Ren

• Deep Adversarial Defense Against Multilevel-Lp Attacks

  Ren Wang, Yuxuan Li, Alfred Hero

• Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays Off

  Levente Halmosi, Bálint Mohos, Márk Jelasity

• Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses

  Yuxin Yang, Qiang Li, Jinyuan Jia, Yuan Hong, Binghui Wang

• PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning

  Sizai Hou, Songze Li, Tayyebeh Jahani-Nezhad, Giuseppe Caire

• DeCE: Deceptive Cross-Entropy Loss Designed for Defending Backdoor Attacks

  Guang Yang, Yu Zhou, Xiang Chen, Xiangyu Zhang, Terry Yue Zhuo, David Lo, Taolue Chen

• CEIPA: Counterfactual Explainable Incremental Prompt Attack Analysis on Large Language Models

  Dong Shu, Mingyu Jin, Tianle Chen, Chong Zhang, Yongfeng Zhang

• BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning

  Ning Wang, Shanghao Shi, Yang Xiao, Yimin Chen, Y. Thomas Hou, Wenjing Lou

• MaPPing Your Model: Assessing the Impact of Adversarial Attacks on LLM-based Programming Assistants

  John Heibel, Daniel Lowd

2024-07-11

• Prediction Exposes Your Face: Black-box Model Inversion via Prediction Alignment

  Yufan Liu, Wanqian Zhang, Dayan Wu, Zheng Lin, Jingzi Gu, Weiping Wang

• Enhancing Robustness of Vision-Language Models through Orthogonality Learning and Cross-Regularization

  Jinlong Li, Zequn Jie, Elisa Ricci, Lin Ma, Nicu Sebe

• Rethinking the Threat and Accessibility of Adversarial Attacks against Face Recognition Systems

  Yuxin Cao, Yumeng Zhu, Derui Wang, Sheng Wen, Minhui Xue, Jin Lu, Hao Ge

• Boosting Adversarial Transferability for Skeleton-based Action Recognition via Exploring the Model Posterior Space

  Yunfeng Diao, Baiqi Wu, Ruixuan Zhang, Xun Yang, Meng Wang, He Wang

• How to beat a Bayesian adversary

  Zihan Ding, Kexin Jin, Jonas Latz, Chenguang Liu

• Model-agnostic clean-label backdoor mitigation in cybersecurity environments

  Giorgio Severi, Simona Boboila, John Holodnak, Kendra Kratkiewicz, Rauf Izmailov, Alina Oprea

• Enhancing Privacy of Spatiotemporal Federated Learning against Gradient Inversion Attacks

  Lele Zheng, Yang Cao, Renhe Jiang, Kenjiro Taura, Yulong Shen, Sheng Li, Masatoshi Yoshikawa

• A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes

  Md Mashrur Arifin, Md Shoaib Ahmed, Tanmai Kumar Ghosh, Jun Zhuang, Jyh-haw Yeh

• Deep Learning for Network Anomaly Detection under Data Contamination: Evaluating Robustness and Mitigating Performance Degradation

  D'Jeff K. Nkashama, Jordan Masakuna Félicien, Arian Soltani, Jean-Charles Verdier, Pierre-Martin Tardif, Marc Frappier, Froduald Kabanza

2024-07-10

• Tuning Vision-Language Models with Candidate Labels by Prompt Alignment

  Zhifang Zhang, Beibei Li

• Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization

  Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He

• Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities

  Tianjie Ju, Yiting Wang, Xinbei Ma, Pengzhou Cheng, Haodong Zhao, Yulong Wang, Lifeng Liu, Jian Xie, Zhuosheng Zhang, Gongshen Liu

• Decompose and Compare Consistency: Measuring VLMs' Answer Reliability via Task-Decomposition Consistency Comparison

  Qian Yang, Weixiang Yan, Aishwarya Agrawal

• Mitigating Backdoor Attacks using Activation-Guided Model Editing

  Felix Hsieh, Huy H. Nguyen, AprilPyone MaungMaung, Dmitrii Usynin, Isao Echizen

2024-07-09

• A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification

  Lu Zhang, Sangarapillai Lambotharan, Gan Zheng, Guisheng Liao, Ambra Demontis, Fabio Roli

• Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspective

  Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan, Xueqi Cheng

• Hiding Local Manipulations on SAR Images: a Counter-Forensic Attack

  Sara Mandelli, Edoardo Daniele Cannas, Paolo Bestagini, Stefano Tebaldini, Stefano Tubaro

• Universal Multi-view Black-box Attack against Object Detectors via Layout Optimization

  Donghua Wang, Wen Yao, Tingsong Jiang, Chao Li, Xiaoqian Chen

• Improving the Transferability of Adversarial Examples by Feature Augmentation

  Donghua Wang, Wen Yao, Tingsong Jiang, Xiaohu Zheng, Junqi Wu, Xiaoqian Chen

• AstroSpy: On detecting Fake Images in Astronomy via Joint Image-Spectral Representations

  Mohammed Talha Alam, Raza Imam, Mohsen Guizani, Fakhri Karray

• Towards Physics-informed Cyclic Adversarial Multi-PSF Lensless Imaging

  Abeer Banerjee, Sanjay Singh

• Event Trojan: Asynchronous Event-based Backdoor Attacks

  Ruofei Wang, Qing Guo, Haoliang Li, Renjie Wan

• Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning

  Yuqi Jia, Minghong Fang, Hongbin Liu, Jinghuai Zhang, Neil Zhenqiang Gong

2024-07-08

• $R^2$-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning

  Mintong Kang, Bo Li

• KG-FPQ: Evaluating Factuality Hallucination in LLMs with Knowledge Graph-based False Premise Questions

  Yanxu Zhu, Jinlin Xiao, Yuhang Wang, Jitao Sang

• Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise

  Bidur Khanal, Tianhong Dai, Binod Bhattarai, Cristian Linte

• Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics

  Elena Camuffo, Umberto Michieli, Simone Milani, Jijoong Moon, Mete Ozay

• FORAY: Towards Effective Attack Synthesis against Deep Logical Vulnerabilities in DeFi Protocols

  Hongbo Wen, Hanzhi Liu, Jiaxin Song, Yanju Chen, Wenbo Guo, Yu Feng

2024-07-07

• Gradient Diffusion: A Perturbation-Resilient Gradient Leakage Attack

  Xuan Liu, Siqi Cai, Qihua Zhou, Song Guo, Ruibin Li, Kaiwei Lin

• Evolutionary Trigger Detection and Lightweight Model Repair Based Backdoor Defense

  Qi Zhou, Zipeng Ye, Yubo Tang, Wenjian Luo, Yuhui Shi, Yan Jia

2024-07-06

• BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Records

  Weimin Lyu, Zexin Bi, Fusheng Wang, Chao Chen

2024-07-05

• Controlling Whisper: Universal Acoustic Adversarial Attacks to Control Speech Foundation Models

  Vyas Raina, Mark Gales

• T2IShield: Defending Against Backdoors on Text-to-Image Diffusion Models

  Zhongqi Wang, Jie Zhang, Shiguang Shan, Xilin Chen

• Self-Supervised Representation Learning for Adversarial Attack Detection

  Yi Li, Plamen Angelov, Neeraj Suri

• Late Breaking Results: Fortifying Neural Networks: Safeguarding Against Adversarial Attacks with Stochastic Computing

  Faeze S. Banitaba, Sercan Aygun, M. Hassan Najafi

• Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape

  Tuan Nguyen, Dung Thuy Nguyen, Khoa D Doan, Kok-Seng Wong

2024-07-04

• Adversarial Robustness of VAEs across Intersectional Subgroups

  Chethan Krishnamurthy Ramanaik, Arjun Roy, Eirini Ntoutsi

• Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Models

  Yuyan Chen, Qiang Fu, Yichen Yuan, Zhihao Wen, Ge Fan, Dayiheng Liu, Dongmei Zhang, Zhixu Li, Yanghua Xiao

• Securing Multi-turn Conversational Language Models Against Distributed Backdoor Triggers

  Terry Tong, Jiashu Xu, Qin Liu, Muhao Chen

• Defense Against Syntactic Textual Backdoor Attacks with Token Substitution

  Xinglin Li, Xianwen He, Yao Li, Minhao Cheng

• DART: Deep Adversarial Automated Red Teaming for LLM Safety

  Bojian Jiang, Yi Jing, Tianhao Shen, Qing Yang, Deyi Xiong

• TrackPGD: A White-box Attack using Binary Masks against Robust Transformer Trackers

  Fatemeh Nourilenjan Nokabadi, Yann Batiste Pequignot, Jean-Francois Lalonde, Christian Gagné

• Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness

  Kejia Zhang, Juanjuan Weng, Yuanzheng Cai, Zhiming Luo, Shaozi Li

• Future Events as Backdoor Triggers: Investigating Temporal Vulnerabilities in LLMs

  Sara Price, Arjun Panickssery, Sam Bowman, Asa Cooper Stickland

2024-07-03

• Self-Evaluation as a Defense Against Adversarial Attacks on LLMs

  Hannah Brown, Leon Lin, Kenji Kawaguchi, Michael Shieh

• Safe Unlearning: A Surprisingly Effective and Generalizable Solution to Defend Against Jailbreak Attacks

  Zhexin Zhang, Junxiao Yang, Pei Ke, Shiyao Cui, Chujie Zheng, Hongning Wang, Minlie Huang

• JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasets

  Zhihua Jin, Shiyi Liu, Haotian Li, Xun Zhao, Huamin Qu

• SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing

  Meiyu Zhong, Ravi Tandon

• A Wolf in Sheep's Clothing: Practical Black-box Adversarial Attacks for Evading Learning-based Windows Malware Detection in the Wild

  Xiang Ling, Zhiyu Wu, Bin Wang, Wei Deng, Jingzheng Wu, Shouling Ji, Tianyue Luo, Yanjun Wu

• Soft Begging: Modular and Efficient Shielding of LLMs against Prompt Injection and Jailbreaking based on Prompt Tuning

  Simon Ostermann, Kevin Baum, Christoph Endres, Julia Masloh, Patrick Schramowski

2024-07-02

• EvolBA: Evolutionary Boundary Attack under Hard-label Black Box condition

  Ayane Tajima, Satoshi Ono

• Adversarial Magnification to Deceive Deepfake Detection through Super Resolution

  Davide Alessandro Coccomini, Roberto Caldelli, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro

• Parameter Matching Attack: Enhancing Practical Applicability of Availability Attacks

  Yu Zhe, Jun Sakuma

• Face Reconstruction Transfer Attack as Out-of-Distribution Generalization

  Yoon Gyo Jung, Jaewoo Park, Xingbo Dong, Hojin Park, Andrew Beng Jin Teoh, Octavia Camps

• Towards More Realistic Extraction Attacks: An Adversarial Perspective

  Yash More, Prakhar Ganesh, Golnoosh Farnadi

• Is Your AI-Generated Code Really Safe? Evaluating Large Language Models on Secure Code Generation with CodeSecEval

  Jiexin Wang, Xitong Luo, Liuwen Cao, Hongkui He, Hailin Huang, Jiayuan Xie, Adam Jatowt, Yi Cai

2024-07-01

• Multi-View Black-Box Physical Attacks on Infrared Pedestrian Detectors Using Adversarial Infrared Grid

  Kalibinuer Tiliwalidi, Chengyin Hu, Weiwen Shi

• Learning Robust 3D Representation from CLIP via Dual Denoising

  Shuqing Luo, Bowen Qu, Wei Gao

• Semantic-guided Adversarial Diffusion Model for Self-supervised Shadow Removal

  Ziqi Zeng, Chen Zhao, Weiling Cai, Chenyu Dong

• Unveiling the Unseen: Exploring Whitebox Membership Inference through the Lens of Explainability

  Chenxi Li, Abhinav Kumar, Zhen Guo, Jie Hou, Reza Tourani

2024-06-30

• Unveiling Glitches: A Deep Dive into Image Encoding Bugs within CLIP

  Ayush Ranjan, Daniel Wen, Karthik Bhat

• Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness

  Yiquan Li, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Bo Li, Chaowei Xiao

• A Whole-Process Certifiably Robust Aggregation Method Against Backdoor Attacks in Federated Learning

  Anqi Zhou, Yezheng Liu, Yidong Chai, Hongyi Zhu, Xinyue Ge, Yuanchun Jiang, Meng Wang

2024-06-29

• Query-Efficient Hard-Label Black-Box Attack against Vision Transformers

  Chao Zhou, Xiaowen Shi, Yuan-Gen Wang

2024-06-28

• Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness

  Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung, Che-Rung Lee

• Deceptive Diffusion: Generating Synthetic Adversarial Examples

  Lucas Beerens, Catherine F. Higham, Desmond J. Higham

• Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation

  Danny Halawi, Alexander Wei, Eric Wallace, Tony T. Wang, Nika Haghtalab, Jacob Steinhardt

• IDT: Dual-Task Adversarial Attacks for Privacy Protection

  Pedro Faustini, Shakila Mahjabin Tonni, Annabelle McIver, Qiongkai Xu, Mark Dras

• NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations

  Junkai Chen, Zhenhao Li, Xing Hu, Xin Xia

• GM-DF: Generalized Multi-Scenario Deepfake Detection

  Yingxin Lai, Zitong Yu, Jing Yang, Bin Li, Xiangui Kang, Linlin Shen

• AstMatch: Adversarial Self-training Consistency Framework for Semi-Supervised Medical Image Segmentation

  Guanghao Zhu, Jing Zhang, Juanxiu Liu, Xiaohui Du, Ruqian Hao, Yong Liu, Lin Liu

• Backdoor Attack in Prompt-Based Continual Learning

  Trang Nguyen, Anh Tran, Nhat Ho

• Virtual Context: Enhancing Jailbreak Attacks with Special Token Injection

  Yuqi Zhou, Lin Lu, Hanchi Sun, Pan Zhou, Lichao Sun

• DiffuseDef: Improved Robustness to Adversarial Attacks

  Zhenhao Li, Marek Rei, Lucia Specia

2024-06-27

• Rethinking harmless refusals when fine-tuning foundation models

  Florin Pop, Judd Rosenblatt, Diogo Schwerz de Lucena, Michael Vaiana

• Data Poisoning Attacks to Locally Differentially Private Frequent Itemset Mining Protocols

  Wei Tong, Haoyu Chen, Jiacheng Niu, Sheng Zhong

2024-06-26

• Poisoned LangChain: Jailbreak LLMs by LangChain

  Ziqiu Wang, Jun Liu, Shengkai Zhang, Yang Yang

• MALSIGHT: Exploring Malicious Source Code and Benign Pseudocode for Iterative Binary Malware Summarization

  Haolang Lu, Hongrui Peng, Guoshun Nan, Jiaoyang Cui, Cheng Wang, Weifei Jin

• WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models

  Liwei Jiang, Kavel Rao, Seungju Han, Allyson Ettinger, Faeze Brahman, Sachin Kumar, Niloofar Mireshghallah, Ximing Lu, Maarten Sap, Yejin Choi, Nouha Dziri

• SafeAligner: Safety Alignment against Jailbreak Attacks via Response Disparity Guidance

  Caishuang Huang, Wanxu Zhao, Rui Zheng, Huijie Lv, Shihan Dou, Sixian Li, Xiao Wang, Enyu Zhou, Junjie Ye, Yuming Yang, Tao Gui, Qi Zhang, Xuanjing Huang

2024-06-25

• Machine Unlearning Fails to Remove Data Poisoning Attacks

  Martin Pawelczyk, Jimmy Z. Di, Yiwei Lu, Gautam Kamath, Ayush Sekhari, Seth Neel

• Diffusion-based Adversarial Purification for Intrusion Detection

  Mohamed Amine Merzouk, Erwan Beurier, Reda Yaich, Nora Boulahia-Cuppens, Frédéric Cuppens

• A Text is Worth Several Tokens: Text Embedding from LLMs Secretly Aligns Well with The Key Tokens

  Zhijie Nie, Richong Zhang, Zhanyu Wu

• Inherent Challenges of Post-Hoc Membership Inference for Large Language Models

  Matthieu Meeus, Shubham Jain, Marek Rei, Yves-Alexandre de Montjoye

2024-06-24

• UNICAD: A Unified Approach for Attack Detection, Noise Reduction and Novel Class Identification

  Alvaro Lopez Pellicer, Kittipos Giatgong, Yi Li, Neeraj Suri, Plamen Angelov

• Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances

  Emma Hart, Quentin Renau, Kevin Sim, Mohamad Alissa

• Adversarial Contrastive Decoding: Boosting Safety Alignment of Large Language Models via Opposite Prompt Optimization

  Zhengyue Zhao, Xiaoyun Zhang, Kaidi Xu, Xing Hu, Rui Zhang, Zidong Du, Qi Guo, Yunji Chen

• Evaluating and Analyzing Relationship Hallucinations in LVLMs

  Mingrui Wu, Jiayi Ji, Oucheng Huang, Jiale Li, Yuhang Wu, Xiaoshuai Sun, Rongrong Ji

• Improving robustness to corruptions with multiplicative weight perturbations

  Trung Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski

• Noisy Neighbors: Efficient membership inference attacks against LLMs

  Filippo Galli, Luca Melis, Tommaso Cucinotta

• BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models

  Yi Zeng, Weiyu Sun, Tran Ngoc Huynh, Dawn Song, Bo Li, Ruoxi Jia

• Evaluating the Quality of Hallucination Benchmarks for Large Vision-Language Models

  Bei Yan, Jie Zhang, Zheng Yuan, Shiguang Shan, Xilin Chen

• Automated Adversarial Discovery for Safety Classifiers

  Yash Kumar Lal, Preethi Lahoti, Aradhana Sinha, Yao Qin, Ananth Balashankar

2024-06-23

• Towards unlocking the mystery of adversarial fragility of neural networks

  Jingchao Gao, Raghu Mudumbai, Xiaodong Wu, Jirong Yi, Catherine Xu, Hui Xie, Weiyu Xu

• CBPF: Filtering Poisoned Data Based on Composite Backdoor Attack

  Hanfeng Xia, Haibo Hong, Ruili Wang

• Blind Baselines Beat Membership Inference Attacks for Foundation Models

  Debeshee Das, Jie Zhang, Florian Tramèr

2024-06-22

• Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs

  Jannik Kossen, Jiatong Han, Muhammed Razzak, Lisa Schut, Shreshth Malik, Yarin Gal

• EmoAttack: Emotion-to-Image Diffusion Models for Emotional Backdoor Generation

  Tianyu Wei, Shanmin Pang, Qi Guo, Yizhuo Ma, Qing Guo

• Federated Adversarial Learning for Robust Autonomous Landing Runway Detection

  Yi Li, Plamen Angelov, Zhengxin Yu, Alvaro Lopez Pellicer, Neeraj Suri

• Large Language Models for Link Stealing Attacks Against Graph Neural Networks

  Faqian Guan, Tianqing Zhu, Hui Sun, Wanlei Zhou, Philip S. Yu

• MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries?

  Xirui Li, Hengguang Zhou, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Cho-Jui Hsieh

2024-06-21

• From LLMs to MLLMs: Exploring the Landscape of Multimodal Jailbreaking

  Siyuan Wang, Zhuohan Long, Zhihao Fan, Zhongyu Wei

• Contextual Interaction via Primitive-based Adversarial Training For Compositional Zero-shot Learning

  Suyi Li, Chenyi Jiang, Shidong Wang, Yang Long, Zheng Zhang, Haofeng Zhang

• DataFreeShield: Defending Adversarial Attacks without Training Data

  Hyeyoon Lee, Kanghyun Choi, Dain Kwon, Sunjong Park, Mayoore Selvarasa Jaiswal, Noseong Park, Jonghyun Choi, Jinho Lee

2024-06-20

• Evaluating Implicit Bias in Large Language Models by Attacking From a Psychometric Perspective

  Yuchen Wen, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng

• Enhancing robustness of data-driven SHM models: adversarial training with circle loss

  Xiangli Yang, Xijie Deng, Hanwei Zhang, Yang Zou, Jianxi Yang

• ObscurePrompt: Jailbreaking Large Language Models via Obscure Input

  Yue Huang, Jingyu Tang, Dongping Chen, Bingda Tang, Yao Wan, Lichao Sun, Xiangliang Zhang

• MEAT: Median-Ensemble Adversarial Training for Improving Robustness and Generalization

  Zhaozhe Hu, Jia-Li Yin, Bin Chen, Luojun Lin, Bo-Hao Chen, Ximeng Liu

• Explainable AI Security: Exploring Robustness of Graph Neural Networks to Adversarial Attacks

  Tao Wu, Canyixing Cui, Xingping Xian, Shaojie Qiao, Chao Wang, Lin Yuan, Shui Yu

• Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning

  Yujing Wang, Hainan Zhang, Sijia Wen, Wangjie Qiu, Binghui Guo

• Adaptive Adversarial Cross-Entropy Loss for Sharpness-Aware Minimization

  Tanapat Ratchatorn, Masayuki Tanaka

• Adversaries Can Misuse Combinations of Safe Models

  Erik Jones, Anca Dragan, Jacob Steinhardt

2024-06-19

• AGSOA:Graph Neural Network Targeted Attack Based on Average Gradient and Structure Optimization

  Yang Chen, Bin Zhou

• Bayes' capacity as a measure for reconstruction attacks in federated learning

  Sayan Biswas, Mark Dras, Pedro Faustini, Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi, Parastoo Sadeghi

• Towards Trustworthy Unsupervised Domain Adaptation: A Representation Learning Perspective for Enhancing Robustness, Discrimination, and Generalization

  Jia-Li Yin, Haoyuan Zheng, Ximeng Liu

• Benchmarking Unsupervised Online IDS for Masquerade Attacks in CAN

  Pablo Moriano, Steven C. Hespeler, Mingyan Li, Robert A. Bridges

2024-06-18

• CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models

  Yuetai Li, Zhangchen Xu, Fengqing Jiang, Luyao Niu, Dinuka Sahabandu, Bhaskar Ramasubramanian, Radha Poovendran

• Adversarial Attacks on Large Language Models in Medicine

  Yifan Yang, Qiao Jin, Furong Huang, Zhiyong Lu

• Stealth edits for provably fixing or attacking large language models

  Oliver J. Sutton, Qinghua Zhou, Wei Wang, Desmond J. Higham, Alexander N. Gorban, Alexander Bastounis, Ivan Y. Tyukin

• UIFV: Data Reconstruction Attack in Vertical Federated Learning

  Jirui Yang, Peng Chen, Zhihui Lu, Qiang Duan, Yubing Bao

• Can Go AIs be adversarially robust?

  Tom Tseng, Euan McLean, Kellin Pelrine, Tony T. Wang, Adam Gleave

• ToxiCloakCN: Evaluating Robustness of Offensive Language Detection in Chinese with Cloaking Perturbations

  Yunze Xiao, Yujia Hu, Kenny Tsu Wei Choo, Roy Ka-wei Lee

• Defending Against Social Engineering Attacks in the Age of LLMs

  Lin Ai, Tharindu Kumarage, Amrita Bhattacharjee, Zizhou Liu, Zheng Hui, Michael Davinroy, James Cook, Laura Cassani, Kirill Trapeznikov, Matthias Kirchner, Arslan Basharat, Anthony Hoogs, Joshua Garland, Huan Liu, Julia Hirschberg

• Adversarial Attacks on Multimodal Agents

  Chen Henry Wu, Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried, Aditi Raghunathan

• Attack and Defense of Deep Learning Models in the Field of Web Attack Detection

  Lijia Shi, Shihao Dong

• MaskPure: Improving Defense Against Text Adversaries with Stochastic Purification

  Harrison Gietz, Jugal Kalita

• NoiSec: Harnessing Noise for Security against Adversarial and Backdoor Attacks

  Md Hasan Shahriar, Ning Wang, Y. Thomas Hou, Wenjing Lou

• DLP: towards active defense against backdoor attacks with decoupled learning process

  Zonghao Ying, Bin Wu

• Saliency Attention and Semantic Similarity-Driven Adversarial Perturbation

  Hetvi Waghela, Jaydip Sen, Sneha Rakshit

2024-06-17

• Adversarial Style Augmentation via Large Language Model for Robust Fake News Detection

  Sungwon Park, Sungwon Han, Meeyoung Cha

• Knowledge-to-Jailbreak: One Knowledge Point Worth One Attack

  Shangqing Tu, Zhuoran Pan, Wenxuan Wang, Zhexin Zhang, Yuliang Sun, Jifan Yu, Hongning Wang, Lei Hou, Juanzi Li

• "Not Aligned" is Not "Malicious": Being Careful about Hallucinations of Large Language Models' Jailbreak

  Lingrui Mei, Shenghua Liu, Yiwei Wang, Baolong Bi, Jiayi Mao, Xueqi Cheng

• Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness

  Kejia Zhang, Juanjuan Weng, Junwei Wu, Guoqing Yang, Shaozi Li, Zhiming Luo

• A First Physical-World Trajectory Prediction Attack via LiDAR-induced Deceptions in Autonomous Driving

  Yang Lou, Yi Zhu, Qun Song, Rui Tan, Chunming Qiao, Wei-Bin Lee, Jianping Wang

• Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness

  Maayan Ehrenberg, Roy Ganz, Nir Rosenfeld

• Obfuscating IoT Device Scanning Activity via Adversarial Example Generation

  Haocong Li, Yaxin Zhang, Long Cheng, Wenjia Niu, Haining Wang, Qiang Li

• Is poisoning a real threat to LLM alignment? Maybe more so than you think

  Pankayaraj Pathmanathan, Souradip Chakraborty, Xiangyu Liu, Yongyuan Liang, Furong Huang

• Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI

  Robert Hönig, Javier Rando, Nicholas Carlini, Florian Tramèr

• ChatBug: A Common Vulnerability of Aligned LLMs Induced by Chat Templates

  Fengqing Jiang, Zhangchen Xu, Luyao Niu, Bill Yuchen Lin, Radha Poovendran

2024-06-16

• KGPA: Robustness Evaluation for Large Language Models via Cross-Domain Knowledge Graphs

  Aihua Pei, Zehua Yang, Shunan Zhu, Ruoxi Cheng, Ju Jia, Lina Wang

• Imperceptible Rhythm Backdoor Attacks: Exploring Rhythm Transformation for Embedding Undetectable Vulnerabilities on Speech Recognition

  Wenhan Yao, Jiangkun Yang, Yongqiang He, Jia Liu, Weiping Wen

• RUPBench: Benchmarking Reasoning Under Perturbations for Robustness Evaluation in Large Language Models

  Yuqing Wang, Yun Zhao

• Imperceptible Face Forgery Attack via Adversarial Semantic Mask

  Decheng Liu, Qixuan Su, Chunlei Peng, Nannan Wang, Xinbo Gao

• Improving Adversarial Robustness via Decoupled Visual Representation Masking

  Decheng Liu, Tao Chen, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao

2024-06-15

• Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions

  Xiao Yang, Gaolei Li, Jianhua Li

• Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models

  Rui Ye, Jingyi Chai, Xiangrui Liu, Yaodong Yang, Yanfeng Wang, Siheng Chen

• Trading Devil: Robust backdoor attack via Stochastic investment models and Bayesian approach

  Orson Mengara

• E-SAGE: Explainability-based Defense Against Backdoor Attacks on Graph Neural Networks

  Dingqiang Yuan, Xiaohua Xu, Lei Yu, Tongchang Han, Rongchang Li, Meng Han

2024-06-14

• Robust Model-Based Reinforcement Learning with an Adversarial Auxiliary Model

  Siemen Herremans, Ali Anwar, Siegfried Mercelis

• Bag of Lies: Robustness in Continuous Pre-training BERT

  Ine Gevers, Walter Daelemans

• Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Networks

  Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang

• Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis

  Zhang Chen, Luca Demetrio, Srishti Gupta, Xiaoyi Feng, Zhaoqiang Xia, Antonio Emanuele Cinà, Maura Pintor, Luca Oneto, Ambra Demontis, Battista Biggio, Fabio Roli

• Semantic Membership Inference Attack against Large Language Models

  Hamid Mozaffari, Virendra J. Marathe

• Watch the Watcher! Backdoor Attacks on Security-Enhancing Diffusion Models

  Changjiang Li, Ren Pang, Bochuan Cao, Jinghui Chen, Fenglong Ma, Shouling Ji, Ting Wang

• PRISM: A Design Framework for Open-Source Foundation Model Safety

  Terrence Neumann, Bryan Jones

• Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples

  Saiyue Lyu, Shadab Shaikh, Frederick Shpilevskiy, Evan Shelhamer, Mathias Lécuyer

2024-06-13

• Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model

  Jiayang Meng, Tao Huang, Hong Chen, Cuiping Li

2024-06-12

• Graph Transductive Defense: a Two-Stage Defense for Graph Membership Inference Attacks

  Peizhi Niu, Chao Pan, Siheng Chen, Olgica Milenkovic

• Asynchronous Voice Anonymization Using Adversarial Perturbation On Speaker Embedding

  Rui Wang, Liping Chen, Kong AiK Lee, Zhen-Hua Ling

• Adversarial Evasion Attack Efficiency against Large Language Models

  João Vitorino, Eva Maia, Isabel Praça

• Are Objective Explanatory Evaluation metrics Trustworthy? An Adversarial Analysis

  Prithwijit Chowdhury, Mohit Prabhushankar, Ghassan AlRegib, Mohamed Deriche

• Adversarial Patch for 3D Local Feature Extractor

  Yu Wen Pao, Li Chang Lai, Hong-Yi Lin

• Transformation-Dependent Adversarial Attacks

  Yaoteng Tan, Zikui Cai, M. Salman Asif

• On Evaluating Adversarial Robustness of Volumetric Medical Segmentation Models

  Hashmat Shadab Malik, Numan Saeed, Asif Hanif, Muzammal Naseer, Mohammad Yaqub, Salman Khan, Fahad Shahbaz Khan

• RRLS : Robust Reinforcement Learning Suite

  Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson

• Genetic Column Generation for Computing Lower Bounds for Adversarial Classification

  Maximilian Penka

• Graph Transductive Defense: a Two-Stage Defense for Graph Membership Inference Attacks

  Peizhi Niu, Chao Pan, Siheng Chen, Olgica Milenkovic

• Adversarial Evasion Attack Efficiency against Large Language Models

  João Vitorino, Eva Maia, Isabel Praça

• Are Objective Explanatory Evaluation metrics Trustworthy? An Adversarial Analysis

  Prithwijit Chowdhury, Mohit Prabhushankar, Ghassan AlRegib, Mohamed Deriche

• Adversarial Patch for 3D Local Feature Extractor

  Yu Wen Pao, Li Chang Lai, Hong-Yi Lin

• AdaNCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer

  Yitao Xu, Tong Zhang, Sabine Süsstrunk

• Transformation-Dependent Adversarial Attacks

  Yaoteng Tan, Zikui Cai, M. Salman Asif

• On Evaluating Adversarial Robustness of Volumetric Medical Segmentation Models

  Hashmat Shadab Malik, Numan Saeed, Asif Hanif, Muzammal Naseer, Mohammad Yaqub, Salman Khan, Fahad Shahbaz Khan

• Genetic Column Generation for Computing Lower Bounds for Adversarial Classification

  Maximilian Penka

• Unique Security and Privacy Threats of Large Language Model: A Comprehensive Survey

  Shang Wang, Tianqing Zhu, Bo Liu, Ding Ming, Xu Guo, Dayong Ye, Wanlei Zhou

• I Don't Know You, But I Can Catch You: Real-Time Defense against Diverse Adversarial Patches for Object Detectors

  Zijin Lin, Yue Zhao, Kai Chen, Jinwen He

• Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries

  Yu-Hsiang Huang, Yuche Tsai, Hsiang Hsiao, Hong-Yi Lin, Shou-De Lin

2024-06-11

• Dual Thinking and Perceptual Analysis of Deep Learning Models using Human Adversarial Examples

  Kailas Dayanandan, Anand Sinha, Brejesh Lall

• Benchmarking Trustworthiness of Multimodal Large Language Models: A Comprehensive Study

  Yichi Zhang, Yao Huang, Yitong Sun, Chang Liu, Zhe Zhao, Zhengwei Fang, Yifan Wang, Huanran Chen, Xiao Yang, Xingxing Wei, Hang Su, Yinpeng Dong, Jun Zhu

• Merging Improves Self-Critique Against Jailbreak Attacks

  Victor Gallego

• AudioMarkBench: Benchmarking Robustness of Audio Watermarking

  Hongbin Liu, Moyang Guo, Zhengyuan Jiang, Lun Wang, Neil Zhenqiang Gong

• Erasing Radio Frequency Fingerprinting via Active Adversarial Perturbation

  Zhaoyi Lu, Wenchao Xu, Ming Tu, Xin Xie, Cunqing Hua, Nan Cheng

• Out-Of-Context Prompting Boosts Fairness and Robustness in Large Language Model Predictions

  Leonardo Cotta, Chris J. Maddison

• Adversarial Machine Unlearning

  Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu

• Out-Of-Context Prompting Boosts Fairness and Robustness in Large Language Model Predictions

  Leonardo Cotta, Chris J. Maddison

• Adversarial Machine Unlearning

  Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu

2024-06-10

• Chain-of-Scrutiny: Detecting Backdoor Attacks for Large Language Models

  Xi Li, Yusen Zhang, Renze Lou, Chen Wu, Jiaqi Wang

• Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning

  Xiaoting Lyu, Yufei Han, Wei Wang, Jingkai Liu, Yongsheng Zhu, Guangquan Xu, Jiqiang Liu, Xiangliang Zhang

• Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness

  Dingrong Wang, Hitesh Sapkota, Zhiqiang Tao, Qi Yu

• An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection

  Shenao Yan, Shen Wang, Yue Duan, Hanbin Hong, Kiho Lee, Doowon Kim, Yuan Hong

• A Survey of Backdoor Attacks and Defenses on Large Language Models: Implications for Security Measures

  Shuai Zhao, Meihuizi Jia, Zhongliang Guo, Leilei Gan, Jie Fu, Yichao Feng, Fengjun Pan, Luu Anh Tuan

2024-06-09

• PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection

  Wei Li, Pin-Yu Chen, Sijia Liu, Ren Wang

• Injecting Undetectable Backdoors in Deep Learning and Language Models

  Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou, Katerina Sotiraki, Grigoris Velegkas, Manolis Zampetakis

• DMS: Addressing Information Loss with More Steps for Pragmatic Adversarial Attacks

  Zhiyu Zhu, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Huaming Chen

• Artificial Intelligence as the New Hacker: Developing Agents for Offensive Security

  Leroy Jacob Valencia

• DMS: Addressing Information Loss with More Steps for Pragmatic Adversarial Attacks

  Zhiyu Zhu, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Huaming Chen

2024-06-08

• SelfDefend: LLMs Can Defend Themselves against Jailbreaking in a Practical Manner

  Xunguang Wang, Daoyuan Wu, Zhenlan Ji, Zongjie Li, Pingchuan Ma, Shuai Wang, Yingjiu Li, Yang Liu, Ning Liu, Juergen Rahmel

• Enhancing Adversarial Transferability via Information Bottleneck Constraints

  Biqing Qi, Junqi Gao, Jianxing Liu, Ligang Wu, Bowen Zhou

• Exploring Adversarial Robustness of Deep State Space Models

  Biqing Qi, Yang Luo, Junqi Gao, Pengfei Li, Kai Tian, Zhiyuan Ma, Bowen Zhou

• Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability

  Junqi Gao, Biqing Qi, Yao Li, Zhichang Guo, Dong Li, Yuming Xing, Dazhi Zhang

• Adversarial flows: A gradient flow characterization of adversarial attacks

  Lukas Weigand, Tim Roith, Martin Burger

2024-06-07

• Sales Whisperer: A Human-Inconspicuous Attack on LLM Brand Recommendations

  Weiran Lin, Anna Gerchanovsky, Omer Akgul, Lujo Bauer, Matt Fredrikson, Zifan Wang

• ADBA:Approximation Decision Boundary Approach for Black-Box Adversarial Attacks

  Feiyang Wang, Xingquan Zuo, Hai Huang, Gang Chen

• Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks

  Lanzino Romeo, Fontana Federico, Diko Anxhelo, Marini Marco Raoul, Cinque Luigi

• The Price of Implicit Bias in Adversarially Robust Generalization

  Nikolaos Tsilivis, Natalie Frank, Nathan Srebro, Julia Kempe

• Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs

  Fan Liu, Zhao Xu, Hao Liu

2024-06-06

• Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection

  Yinting Wu, Pai Peng, Bo Cai, Le Li

• Improving Alignment and Robustness with Short Circuiting

  Andy Zou, Long Phan, Justin Wang, Derek Duenas, Maxwell Lin, Maksym Andriushchenko, Rowan Wang, Zico Kolter, Matt Fredrikson, Dan Hendrycks

• Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt

  Zonghao Ying, Aishan Liu, Tianyuan Zhang, Zhengmin Yu, Siyuan Liang, Xianglong Liu, Dacheng Tao

• AutoJailbreak: Exploring Jailbreak Attacks and Defenses through a Dependency Lens

  Lin Lu, Hai Yan, Zenghui Yuan, Jiawen Shi, Wenqi Wei, Pin-Yu Chen, Pan Zhou

• PromptFix: Few-shot Backdoor Removal via Adversarial Prompt Tuning

  Tianrong Zhang, Zhaohan Xi, Ting Wang, Prasenjit Mitra, Jinghui Chen

2024-06-05

• FREA: Feasibility-Guided Generation of Safety-Critical Scenarios with Reasonable Adversariality

  Keyu Chen, Yuheng Lei, Hao Cheng, Haoran Wu, Wenchao Sun, Sifa Zheng

• BadAgent: Inserting and Activating Backdoor Attacks in LLM Agents

  Yifei Wang, Dizhan Xue, Shengjie Zhang, Shengsheng Qian

• DifAttack++: Query-Efficient Black-Box Adversarial Attack via Hierarchical Disentangled Feature Space in Cross Domain

  Jun Liu, Jiantao Zhou, Jiandian Zeng, Jinyu Tian

• VQUNet: Vector Quantization U-Net for Defending Adversarial Atacks by Regularizing Unwanted Noise

  Zhixun He, Mukesh Singhal

• ZeroPur: Succinct Training-Free Adversarial Purification

  Xiuli Bi, Zonglin Yang, Bo Liu, Xiaodong Cun, Chi-Man Pun, Pietro Lio, Bin Xiao

• Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections

  Zihan Luo, Hong Huang, Yongkang Zhou, Jiping Zhang, Nuo Chen

• Distributional Adversarial Loss

  Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain

• Defending Large Language Models Against Attacks With Residual Stream Activation Analysis

  Amelia Kawasaki, Andrew Davis, Houssam Abbas

• Mutual Information Guided Backdoor Mitigation for Pre-trained Encoders

  Tingxu Han, Weisong Sun, Ziqi Ding, Chunrong Fang, Hanwei Qian, Jiaxun Li, Zhenyu Chen, Xiangyu Zhang

2024-06-04

• Certifiably Byzantine-Robust Federated Conformal Prediction

  Mintong Kang, Zhen Lin, Jimeng Sun, Cao Xiao, Bo Li

• CR-UTP: Certified Robustness against Universal Text Perturbations

  Qian Lou, Xin Liang, Jiaqi Xue, Yancheng Zhang, Rui Xie, Mengxin Zheng

• QROA: A Black-Box Query-Response Optimization Attack on LLMs

  Hussein Jawad, Nicolas J.-B. BRUNEL (LaMME)

• MoLA: Motion Generation and Editing with Latent Diffusion Enhanced by Adversarial Training

  Kengo Uchida, Takashi Shibuya, Yuhta Takida, Naoki Murata, Shusuke Takahashi, Yuki Mitsufuji

• SVASTIN: Sparse Video Adversarial Attack via Spatio-Temporal Invertible Neural Networks

  Yi Pan, Jun-Jie Huang, Zihan Chen, Wentao Zhao, Ziyue Wang

• Advancing Generalized Transfer Attack with Initialization Derived Bilevel Optimization and Dynamic Sequence Truncation

  Yaohua Liu, Jiaxin Gao, Xuan Liu, Xianghao Jiao, Xin Fan, Risheng Liu

• Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing

  Youwei Shu, Xi Xiao, Derui Wang, Yuxin Cao, Siji Chen, Jason Xue, Linyi Li, Bo Li

• Ai-Sampler: Adversarial Learning of Markov kernels with involutive maps

  Evgenii Egorov, Ricardo Valperga, Efstratios Gavves

• Auditing Privacy Mechanisms via Label Inference Attacks

  Róbert István Busa-Fekete, Travis Dick, Claudio Gentile, Andrés Muñoz Medina, Adam Smith, Marika Swanberg

2024-06-03

• BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

  Jiaqi Xue, Mengxin Zheng, Yebowen Hu, Fei Liu, Xun Chen, Qian Lou

• FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation

  Hanlin Gu, Jiahuan Luo, Yan Kang, Yuan Yao, Gongxi Zhu, Bowen Li, Lixin Fan, Qiang Yang

• Are AI-Generated Text Detectors Robust to Adversarial Perturbations?

  Guanhua Huang, Yuchen Zhang, Zhe Li, Yongjian You, Mingze Wang, Zhouwang Yang

• PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration

  Ziqian Zeng, Jianwei Wang, Zhengdong Lu, Huiping Zhuang, Cen Chen

• Exploring Vulnerabilities and Protections in Large Language Models: A Survey

  Frank Weizhen Liu, Chenhui Hu

• Are you still on track!? Catching LLM Task Drift with Activations

  Sahar Abdelnabi, Aideen Fay, Giovanni Cherubin, Ahmed Salem, Mario Fritz, Andrew Paverd

• Robust Infidelity: When Faithfulness Measures on Masked Language Models Are Misleading

  Evan Crothers, Herna Viktor, Nathalie Japkowicz

• Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast

  Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, Min Lin

• Adversarial 3D Virtual Patches using Integrated Gradients

  Chengzeng You, Zhongyuan Hau, Binbin Xu, Soteris Demetriou

• Accent Conversion in Text-To-Speech Using Multi-Level VAE and Adversarial Training

  Jan Melechovsky, Ambuj Mehrish, Berrak Sisman, Dorien Herremans

• Poisoning Attacks and Defenses in Recommender Systems: A Survey

  Zongwei Wang, Junliang Yu, Min Gao, Guanhua Ye, Shazia Sadiq, Hongzhi Yin

• Constraint-based Adversarial Example Synthesis

  Fang Yu, Ya-Yu Chi, Yu-Fang Chen

• Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers

  Fatemeh Nourilenjan Nokabadi, Jean-François Lalonde, Christian Gagné

• Model for Peanuts: Hijacking ML Models without Training Access is Possible

  Mahmoud Ghorbel, Halima Bouzidi, Ioan Marius Bilasco, Ihsen Alouani

• Safeguarding Large Language Models: A Survey

  Yi Dong, Ronghui Mu, Yanghao Zhang, Siqi Sun, Tianle Zhang, Changshun Wu, Gaojie Jin, Yi Qi, Jinwei Hu, Jie Meng, Saddek Bensalem, Xiaowei Huang

• Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits

  Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Charlie Rogers-Smith, Jeffrey Ladish, Christian Schroeder de Witt

2024-06-02

• Stealing Image-to-Image Translation Models With a Single Query

  Nurit Spingarn-Eliezer, Tomer Michaeli

• Invisible Backdoor Attacks on Diffusion Models

  Sen Li, Junchi Ma, Minhao Cheng

• Generalization Bound and New Algorithm for Clean-Label Backdoor Attack

  Lijia Yu, Shuang Liu, Yibo Miao, Xiao-Shan Gao, Lijun Zhang

• Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data

  Thibault Simonetto, Salah Ghamizi, Maxime Cordy

• Teams of LLM Agents can Exploit Zero-Day Vulnerabilities

  Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang

• A Novel Defense Against Poisoning Attacks on Federated Learning: LayerCAM Augmented with Autoencoder

  Jingjing Zheng, Xin Yuan, Kai Li, Wei Ni, Eduardo Tovar, Jon Crowcroft

2024-06-01

• Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training

  Jiacheng Zhang, Feng Liu, Dawei Zhou, Jingfeng Zhang, Tongliang Liu

• Robust Knowledge Distillation Based on Feature Variance Against Backdoored Teacher Model

  Jinyin Chen, Xiaoming Zhao, Haibin Zheng, Xiao Li, Sheng Xiang, Haifeng Guo

2024-05-31

• Enhancing Jailbreak Attack Against Large Language Models through Silent Tokens

  Jiahao Yu, Haozheng Luo, Jerry Yao-Chieh, Wenbo Guo, Han Liu, Xinyu Xing

• GI-NAS: Boosting Gradient Inversion Attacks through Adaptive Neural Architecture Search

  Wenbo Yu, Hao Fang, Bin Chen, Xiaohang Sui, Chuan Chen, Hao Wu, Shu-Tao Xia, Ke Xu

• Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training

  Feiteng Fang, Yuelin Bai, Shiwen Ni, Min Yang, Xiaojun Chen, Ruifeng Xu

• Certifying Global Robustness for Deep Neural Networks

  You Li, Guannan Zhao, Shuyu Kong, Yunqi He, Hai Zhou

• Disrupting Diffusion: Token-Level Attention Erasure Attack against Diffusion-based Customization

  Yisu Liu, Jinyang An, Wanqian Zhang, Dayan Wu, Jingzi Gu, Zheng Lin, Weiping Wang

• GANcrop: A Contrastive Defense Against Backdoor Attacks in Federated Learning

  Xiaoyun Gan, Shanyu Gan, Taizhi Su, Peng Liu

• ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning

  Zhangchen Xu, Fengqing Jiang, Luyao Niu, Jinyuan Jia, Bo Li, Radha Poovendran

• Improved Techniques for Optimization-Based Jailbreaking on Large Language Models

  Xiaojun Jia, Tianyu Pang, Chao Du, Yihao Huang, Jindong Gu, Yang Liu, Xiaochun Cao, Min Lin

• Investigating and unmasking feature-level vulnerabilities of CNNs to adversarial perturbations

  Davide Coppola, Hwee Kuan Lee

• Query Provenance Analysis for Robust and Efficient Query-based Black-box Attack Defense

  Shaofei Li, Ziqi Zhang, Haomin Jia, Ding Li, Yao Guo, Xiangqun Chen

• BackdoorIndicator: Leveraging OOD Data for Proactive Backdoor Detection in Federated Learning

  Songze Li, Yanbo Dai

• RASE: Efficient Privacy-preserving Data Aggregation against Disclosure Attacks for IoTs

  Zuyan Wang, Jun Tao, Dika Zou

• Exfiltration of personal information from ChatGPT via prompt injection

  Gregory Schwartzman

2024-05-30

• HOLMES: to Detect Adversarial Examples with Multiple Detectors

  Jing Wen

• Efficient LLM-Jailbreaking by Introducing Visual Modality

  Zhenxing Niu, Yuyao Sun, Haodong Ren, Haoxuan Ji, Quan Wang, Xiaoke Ma, Gang Hua, Rong Jin

• Context Injection Attacks on Large Language Models

  Cheng'an Wei, Kai Chen, Yue Zhao, Yujia Gong, Lu Xiang, Shenchen Zhu

• Large Language Model Watermark Stealing With Mixed Integer Programming

  Zhaoxi Zhang, Xiaomei Zhang, Yanjun Zhang, Leo Yu Zhang, Chao Chen, Shengshan Hu, Asif Gill, Shirui Pan

• AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization

  Jiawei Chen, Xiao Yang, Zhengwei Fang, Yu Tian, Yinpeng Dong, Zhaoxia Yin, Hang Su

• DiffPhysBA: Diffusion-based Physical Backdoor Attack against Person Re-Identification in Real-World

  Wenli Sun, Xinyang Jiang, Dongsheng Li, Cairong Zhao

• Typography Leads Semantic Diversifying: Amplifying Adversarial Transferability across Multimodal Large Language Models

  Hao Cheng, Erjia Xiao, Jiahang Cao, Le Yang, Kaidi Xu, Jindong Gu, Renjing Xu

• Unveiling and Mitigating Backdoor Vulnerabilities based on Unlearning Weight Changes and Backdoor Activeness

  Weilin Lin, Li Liu, Shaokui Wei, Jianze Li, Hui Xiong

• BAN: Detecting Backdoors Activated by Adversarial Neuron Noise

  Xiaoyun Xu, Zhuoran Liu, Stefanos Koffas, Shujian Yu, Stjepan Picek

• Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable

  Martin Bertran, Shuai Tang, Michael Kearns, Jamie Morgenstern, Aaron Roth, Zhiwei Steven Wu

• Evaluating the Effectiveness and Robustness of Visual Similarity-based Phishing Detection Models

  Fujiao Ji, Kiho Lee, Hyungjoon Koo, Wenhao You, Euijin Choo, Hyoungshick Kim, Doowon Kim

• Defensive Prompt Patch: A Robust and Interpretable Defense of LLMs against Jailbreak Attacks

  Chen Xiong, Xiangyu Qi, Pin-Yu Chen, Tsung-Yi Ho

• Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generation

  Maya Anderson, Guy Amit, Abigail Goldsteen

• Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters

  Haibo Jin, Andy Zhou, Joe D. Menke, Haohan Wang

• Phantom: General Trigger Attacks on Retrieval Augmented Language Generation

  Harsh Chaudhari, Giorgio Severi, John Abascal, Matthew Jagielski, Christopher A. Choquette-Choo, Milad Nasr, Cristina Nita-Rotaru, Alina Oprea

• Is Synthetic Data all We Need? Benchmarking the Robustness of Models Trained with Synthetic Images

  Krishnakant Singh, Thanush Navaratnam, Jannik Holmer, Simone Schaub-Meyer, Stefan Roth

• Enhancing Adversarial Robustness in SNNs with Sparse Gradients

  Yujia Liu, Tong Bu, Jianhao Ding, Zecheng Hao, Tiejun Huang, Zhaofei Yu

• SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents

  Ethan Rathbun, Christopher Amato, Alina Oprea

2024-05-29

• Leveraging Many-To-Many Relationships for Defending Against Visual-Language Adversarial Attacks

  Futa Waseda, Antonio Tejero-de-Pablos

• EntProp: High Entropy Propagation for Improving Accuracy and Robustness

  Shohei Enomoto

• Verifiably Robust Conformal Prediction

  Linus Jeary, Tom Kuipers, Mehran Hosseini, Nicola Paoletti

• DiveR-CT: Diversity-enhanced Red Teaming with Relaxing Constraints

  Andrew Zhao, Quentin Xu, Matthieu Lin, Shenzhi Wang, Yong-jin Liu, Zilong Zheng, Gao Huang

• Convex neural network synthesis for robustness in the 1-norm

  Ross Drummond, Chris Guiver, Matthew C. Turner

• Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior

  Shuyu Cheng, Yibo Miao, Yinpeng Dong, Xiao Yang, Xiao-Shan Gao, Jun Zhu

• Model Agnostic Defense against Adversarial Patch Attacks on Object Detection in Unmanned Aerial Vehicles

  Saurabh Pathak, Samridha Shrestha, Abdelrahman AlMahmoud

• Robust Entropy Search for Safe Efficient Bayesian Optimization

  Dorina Weichert, Alexander Kister, Patrick Link, Sebastian Houben, Gunar Ernis

• Voice Jailbreak Attacks Against GPT-4o

  Xinyue Shen, Yixin Wu, Michael Backes, Yang Zhang

• PermLLM: Private Inference of Large Language Models within 3 Seconds under WAN

  Fei Zheng, Chaochao Chen, Zhongxuan Han, Xiaolin Zheng

• Node Injection Attack Based on Label Propagation Against Graph Neural Network

  Peican Zhu, Zechen Pan, Keke Tang, Xiaodong Cui, Jinhuan Wang, Qi Xuan

• AI Risk Management Should Incorporate Both Safety and Security

  Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal

• Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies

  Yipu Chen, Haotian Xue, Yongxin Chen

2024-05-28

• Defending Large Language Models Against Jailbreak Attacks via Layer-specific Editing

  Wei Zhao, Zhe Li, Yige Li, Ye Zhang, Jun Sun

• Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding

  Daniel Bethell, Simos Gerasimou, Radu Calinescu, Calum Imrie

• Rethinking Pruning for Backdoor Mitigation: An Optimization Perspective

  Nan Li, Haiyang Yu, Ping Yi

• Magnitude-based Neuron Pruning for Backdoor Defens

  Nan Li, Haoyu Jiang, Ping Yi

• White-box Multimodal Jailbreaks Against Large Vision-Language Models

  Ruofan Wang, Xingjun Ma, Hanxu Zhou, Chuanjun Ji, Guangnan Ye, Yu-Gang Jiang

• ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator

  Junda Zhu, Lingyong Yan, Haibo Shi, Dawei Yin, Lei Sha

• Towards Unified Robustness Against Both Backdoor and Adversarial Attacks

  Zhenxing Niu, Yuyao Sun, Qiguang Miao, Rong Jin, Gang Hua

• Cross-Context Backdoor Attacks against Graph Prompt Learning

  Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor Tsang, Xiangliang Zhang

• Channel Reciprocity Based Attack Detection for Securing UWB Ranging by Autoencoder

  Wenlong Gou, Chuanhang Yu, Juntao Ma, Gang Wu, Vladimir Mordachev

• Learning diverse attacks on large language models for robust red-teaming and safety tuning

  Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain

• Lazy Safety Alignment for Large Language Models against Harmful Fine-tuning

  Tiansheng Huang, Sihao Hu, Fatih Ilhan, Selim Furkan Tekin, Ling Liu

• Improved Generation of Adversarial Examples Against Safety-aligned LLMs

  Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen

• Stochastic Adversarial Networks for Multi-Domain Text Classification

  Xu Wang, Yuan Wu

2024-05-27

• TrojFM: Resource-efficient Backdoor Attacks against Very Large Foundation Models

  Yuzhou. Nie, Yanting. Wang, Jinyuan. Jia, Michael J. De Lucia, Nathaniel D. Bastian, Wenbo. Guo, Dawn. Song

• Tokenization Matters! Degrading Large Language Models through Challenging Their Tokenization

  Dixuan Wang, Yanda Li, Junyuan Jiang, Zepeng Ding, Guochao Jiang, Jiaqing Liang, Deqing Yang

• A One-Layer Decoder-Only Transformer is a Two-Layer RNN: With an Application to Certified Robustness

  Yuhao Zhang, Aws Albarghouthi, Loris D'Antoni

• Exploiting the Layered Intrinsic Dimensionality of Deep Models for Practical Adversarial Training

  Enes Altinisik, Safa Messaoud, Husrev Taha Sencar, Hassan Sajjad, Sanjay Chawla

• Privacy-Aware Visual Language Models

  Laurens Samson, Nimrod Barazani, Sennay Ghebreab, Yuki M. Asano

• Anonymization Prompt Learning for Facial Privacy-Preserving Text-to-Image Generation

  Liang Shi, Jie Zhang, Shiguang Shan

• Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models

  Fengfan Zhou, Qianyu Zhou, Xiangtai Li, Xuequan Lu, Lizhuang Ma, Hefei Ling

• Spectral regularization for adversarially-robust representation learning

  Sheng Yang, Jacob A. Zavatone-Veth, Cengiz Pehlevan

• Safe LoRA: the Silver Lining of Reducing Safety Risks when Fine-tuning Large Language Models

  Chia-Yi Hsu, Yu-Lin Tsai, Chih-Hsun Lin, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang

• The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective

  Nils Philipp Walter, Linara Adilova, Jilles Vreeken, Michael Kamp

• OSLO: One-Shot Label-Only Membership Inference Attacks

  Yuefeng Peng, Jaechul Roh, Subhransu Maji, Amir Houmansadr

• Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models

  ShengYun Peng, Pin-Yu Chen, Matthew Hull, Duen Horng Chau

• TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability

  Fengji Ma, Li Liu, Hei Victor Cheng

• Exploring Backdoor Attacks against Large Language Model-based Decision Making

  Ruochen Jiao, Shaoyuan Xie, Justin Yue, Takami Sato, Lixu Wang, Yixuan Wang, Qi Alfred Chen, Qi Zhu

2024-05-26

• Automatic Jailbreaking of the Text-to-Image Generative AI Systems

  Minseon Kim, Hyomin Lee, Boqing Gong, Huishuai Zhang, Sung Ju Hwang

• Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning

  Xueqing Zhang, Junkai Zhang, Ka-Ho Chow, Juntao Chen, Ying Mao, Mohamed Rahouti, Xiang Li, Yuchen Liu, Wenqi Wei

• Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level

  Runlin Lei, Yuwei Hu, Yuchen Ren, Zhewei Wei

• Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer

  Zhihan Liu, Miao Lu, Shenao Zhang, Boyi Liu, Hongyi Guo, Yingxiang Yang, Jose Blanchet, Zhaoran Wang

• Partial train and isolate, mitigate backdoor attack

  Yong Li, Han Gao

• Pruning for Robust Concept Erasing in Diffusion Models

  Tianyun Yang, Juan Cao, Chang Xu

• Cross-Modality Jailbreak and Mismatched Attacks on Medical Multimodal Large Language Models

  Xijie Huang, Xinyuan Wang, Hantao Zhang, Jiawen Xi, Jingkun An, Hao Wang, Chengwei Pan

2024-05-25

• Diffusion-Reward Adversarial Imitation Learning

  Chun-Mao Lai, Hsiang-Chun Wang, Ping-Chun Hsieh, Yu-Chiang Frank Wang, Min-Hung Chen, Shao-Hua Sun

• Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack

  Mingli Zhu, Siyuan Liang, Baoyuan Wu

• Enhancing Adversarial Transferability Through Neighborhood Conditional Sampling

  Chunlin Qiu, Yiheng Duan, Lingchen Zhao, Qian Wang

• Detecting Adversarial Data via Perturbation Forgery

  Qian Wang, Chen Li, Yuchen Luo, Hefei Ling, Ping Li, Jiazhong Chen, Shijuan Huang, Ning Yu

• Enhancing Consistency-Based Image Generation via Adversarialy-Trained Classification and Energy-Based Discrimination

  Shelly Golan, Roy Ganz, Michael Elad

• R.A.C.E.: Robust Adversarial Concept Erasure for Secure Text-to-Image Diffusion Model

  Changhoon Kim, Kyle Min, Yezhou Yang

• Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness

  Jieren Deng, Hanbin Hong, Aaron Palmer, Xin Zhou, Jinbo Bi, Kaleel Mahmood, Yuan Hong, Derek Aguiar

• Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor

  Shaokui Wei, Hongyuan Zha, Baoyuan Wu

• Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency

  Runqi Lin, Chaojian Yu, Bo Han, Hang Su, Tongliang Liu

• Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection

  M. Saeid HaghighiFard, Sinem Coleri

• Towards Black-Box Membership Inference Attack for Diffusion Models

  Jingwei Li, Jing Dong, Tianxing He, Jingzhao Zhang

• Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Characte

  Siyuan Ma, Weidi Luo, Yu Wang, Xiaogeng Liu, Muhao Chen, Bo Li, Chaowei Xiao

2024-05-24

• How Does Bayes Error Limit Probabilistic Robust Accuracy

  Ruihan Zhang, Jun Sun

• RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation

  Peihua Mai, Ran Yan, Yan Pang

• Coordinated Disclosure for AI: Beyond Security Vulnerabilities

  Sven Cattell, Avijit Ghosh, Lucie-Aimée Kaffee

• Robust Diffusion Models for Adversarial Purification

  Guang Lin, Zerui Tao, Jianhai Zhang, Toshihisa Tanaka, Qibin Zhao

• Certifiably Robust RAG against Retrieval Corruption

  Chong Xiang, Tong Wu, Zexuan Zhong, David Wagner, Danqi Chen, Prateek Mittal

• Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models

  Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu

• BDetCLIP: Multimodal Prompting Contrastive Test-Time Backdoor Detection

  Yuwei Niu, Shuo He, Qi Wei, Feng Liu, Lei Feng

• Scale-Invariant Feature Disentanglement via Adversarial Learning for UAV-based Object Detection

  Fan Liu, Liang Yao, Chuanyi Zhang, Ting Wu, Xinlei Zhang, Jun Zhou, Xiruo Jiang

• Better Membership Inference Privacy Measurement through Discrepancy

  Ruihan Wu, Pengrun Huang, Kamalika Chaudhuri

• Adversarial Attacks on Hidden Tasks in Multi-Task Learning

  Yu Zhe, Rei Nagaike, Daiki Nishiyama, Kazuto Fukuchi, Jun Sakuma

• Decaf: Data Distribution Decompose Attack against Federated Learning

  Zhiyang Dai, Chunyi Zhou, Anmin Fu

• Lost in the Averages: A New Specific Setup to Evaluate Membership Inference Attacks Against Machine Learning Models

  Florent Guépin, Nataša Krčo, Matthieu Meeus, Yves-Alexandre de Montjoye

• DAGER: Exact Gradient Inversion for Large Language Models

  Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev

• Efficient Adversarial Training in LLMs with Continuous Attacks

  Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn

• TrojanForge: Adversarial Hardware Trojan Examples with Reinforcement Learning

  Amin Sarihi, Peter Jamieson, Ahmad Patooghy, Abdel-Hameed A. Badawy

• Adversarial Imitation Learning from Visual Observations using Latent Information

  Vittorio Giammarino, James Queeney, Ioannis Ch. Paschalidis

• Evaluating the Adversarial Robustness of Retrieval-Based In-Context Learning for Large Language Models

  Simon Chi Lok Yu, Jie He, Pasquale Minervini, Jeff Z. Pan

• A Neurosymbolic Framework for Bias Correction in CNNs

  Parth Padalkar, Natalia Ślusarz, Ekaterina Komendantskaya, Gopal Gupta

• Robust width: A lightweight and certifiable adversarial defense

  Jonathan Peck, Bart Goossens

• Can Implicit Bias Imply Adversarial Robustness?

  Hancheng Min, René Vidal

• BadGD: A unified data-centric framework to identify gradient descent vulnerabilities

  Chi-Hua Wang, Guang Cheng

• Robustifying Safety-Aligned Large Language Models through Clean Data Curation

  Xiaoqun Liu, Jiacheng Liang, Muchao Ye, Zhaohan Xi

• ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users

  Guanlin Li, Kangjie Chen, Shudong Zhang, Jie Zhang, Tianwei Zhang

• Large Language Model Sentinel: Advancing Adversarial Robustness by LLM Agent

  Guang Lin, Qibin Zhao

2024-05-23

• Learning to Transform Dynamically for Better Adversarial Transferability

  Rongyi Zhu, Zeliang Zhang, Susan Liang, Zhuo Liu, Chenliang Xu

• Certified Robustness against Sparse Adversarial Perturbations via Data Localization

  Ambar Pal, René Vidal, Jeremias Sulam

• SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines

  Andrea Ponte, Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli

• Semantic-guided Prompt Organization for Universal Goal Hijacking against LLMs

  Yihao Huang, Chong Wang, Xiaojun Jia, Qing Guo, Felix Juefei-Xu, Jian Zhang, Geguang Pu, Yang Liu

• MoGU: A Framework for Enhancing Safety of Open-Sourced LLMs While Preserving Their Usability

  Yanrui Du, Sendong Zhao, Danyang Zhao, Ming Ma, Yuhan Chen, Liangyu Huo, Qing Yang, Dongliang Xu, Bing Qin

• Impact of Non-Standard Unicode Characters on Security and Comprehension in Large Language Models

  Johan S Daniel, Anand Pal

• Unveiling the Achilles' Heel of NLG Evaluators: A Unified Adversarial Framework Driven by Large Language Models

  Yiming Chen, Chen Zhang, Danqing Luo, Luis Fernando D'Haro, Robby T. Tan, Haizhou Li

• Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography

  Nhat Chung, Sensen Gao, Tuan-Anh Vu, Jie Zhang, Aishan Liu, Yun Lin, Jin Song Dong, Qing Guo

• Eidos: Efficient, Imperceptible Adversarial 3D Point Clouds

  Hanwei Zhang, Luo Cheng, Qisong He, Wei Huang, Renjue Li, Ronan Sicre, Xiaowei Huang, Holger Hermanns, Lijun Zhang

• Towards Imperceptible Backdoor Attack in Self-supervised Learning

  Hanrong Zhang, Zhenting Wang, Tingxu Han, Mingyu Jin, Chenlu Zhan, Mengnan Du, Hongwei Wang, Shiqing Ma

• Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy

  Shengfang Zhai, Huanran Chen, Yinpeng Dong, Jiajun Li, Qingni Shen, Yansong Gao, Hang Su, Yang Liu

• Boosting Robustness by Clipping Gradients in Distributed Learning

  Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Ahmed Jellouli, Geovani Rizk, John Stephan

• Identity Inference from CLIP Models using Only Textual Data

  Songze Li, Ruoxi Cheng, Xiaojun Jia

• A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection

  Marco Rando, Luca Demetrio, Lorenzo Rosasco, Fabio Roli

• Nearly Tight Black-Box Auditing of Differentially Private Machine Learning

  Meenatchi Sundaram Muthu Selva Annamalai, Emiliano De Cristofaro

• Generating camera failures as a class of physics-based adversarial examples

  Manav Prabhakar, Jwalandhar Girnar, Arpan Kusari

• Universal Robustness via Median Randomized Smoothing for Real-World Super-Resolution

  Zakariya Chaouai, Mohamed Tamaazousti

2024-05-22

• Adversarial Training via Adaptive Knowledge Amalgamation of an Ensemble of Teachers

  Shayan Mohajer Hamidi, Linfeng Ye

• Safety Alignment for Vision Language Models

  Zhendong Liu, Yuanbi Nie, Yingshui Tan, Xiangyu Yue, Qiushi Cui, Chongjun Wang, Xiaoyong Zhu, Bo Zheng

• DeepNcode: Encoding-Based Protection against Bit-Flip Attacks on Neural Networks

  Patrik Velčický, Jakub Breier, Xiaolu Hou, Mladen Kovačević

• Towards Comprehensive and Efficient Post Safety Alignment of Large Language Models via Safety Patching

  Weixiang Zhao, Yulin Hu, Zhuojun Li, Yang Deng, Yanyan Zhao, Bing Qin, Tat-Seng Chua

• TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models

  Pengzhou Cheng, Yidong Ding, Tianjie Ju, Zongru Wu, Wei Du, Ping Yi, Zhuosheng Zhang, Gongshen Liu

• Towards Certification of Uncertainty Calibration under Adversarial Attacks

  Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz, Philip H.S. Torr, Adel Bibi

• WordGame: Efficient & Effective LLM Jailbreak via Simultaneous Obfuscation in Query and Response

  Tianrong Zhang, Bochuan Cao, Yuanpu Cao, Lu Lin, Prasenjit Mitra, Jinghui Chen

• Adversarial Training of Two-Layer Polynomial and ReLU Activation Networks via Convex Optimization

  Daniel Kuelbs, Sanjay Lall, Mert Pilanci

• Memory Scraping Attack on Xilinx FPGAs: Private Data Extraction from Terminated Processes

  Bharadwaj Madabhushi, Sandip Kundu, Daniel Holcomb

2024-05-21

• Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models

  Jiaqi Li, Qianshan Wei, Chuanyi Zhang, Guilin Qi, Miaozeng Du, Yongrui Chen, Sheng Bi

• Tiny Refinements Elicit Resilience: Toward Efficient Prefix-Model Against LLM Red-Teaming

  Jiaxu Liu, Xiangyu Yin, Sihao Wu, Jianhong Wang, Meng Fang, Xinping Yi, Xiaowei Huang

• Generative AI and Large Language Models for Cyber Security: All Insights You Need

  Mohamed Amine Ferrag, Fatima Alwahedi, Ammar Battah, Bilel Cherif, Abdechakour Mechri, Norbert Tihanyi

• Transparency Distortion Robustness for SOTA Image Segmentation Tasks

  Volker Knauthe, Arne Rak, Tristan Wirth, Thomas Pöllabauer, Simon Metzler, Arjan Kuijper, Dieter W. Fellner

• Nearest is Not Dearest: Towards Practical Defense against Quantization-conditioned Backdoor Attacks

  Boheng Li, Yishuo Cai, Haowei Li, Feng Xue, Zhifeng Li, Yiming Li

• Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical Image

  Zerui Zhang, Zhichao Sun, Zelong Liu, Bo Du, Rui Yu, Zhou Zhao, Yongchao Xu

• Robust Classification via a Single Diffusion Model

  Huanran Chen, Yinpeng Dong, Zhengyi Wang, Xiao Yang, Chengqi Duan, Hang Su, Jun Zhu

• Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllers

  Fan Shi, Chong Zhang, Takahiro Miki, Joonho Lee, Marco Hutter, Stelian Coros

• How to Train a Backdoor-Robust Model on a Poisoned Dataset without Auxiliary Data?

  Yuwen Pu, Jiahao Chen, Chunyi Zhou, Zhou Feng, Qingming Li, Chunqiang Hu, Shouling Ji

• A Stealthy Backdoor Attack for Without-Label-Sharing Split Learning

  Yuwen Pu, Zhuoyuan Ding, Jiahao Chen, Chunyi Zhou, Qingming Li, Chunqiang Hu, Shouling Ji

• Rethinking the Vulnerabilities of Face Recognition Systems:From a Practical Perspective

  Jiahao Chen, Zhiqiang Shen, Yuwen Pu, Chunyi Zhou, Shouling Ji

• GPT-4 Jailbreaks Itself with Near-Perfect Success Using Self-Explanation

  Govind Ramesh, Yao Dou, Wei Xu

• Interactive Simulations of Backdoors in Neural Networks

  Peter Bajcsy, Maxime Bros

• EmInspector: Combating Backdoor Attacks in Federated Self-Supervised Learning Through Embedding Inspection

  Yuwen Qian, Shuchi Wu, Kang Wei, Ming Ding, Di Xiao, Tao Xiang, Chuan Ma, Song Guo

• A novel reliability attack of Physical Unclonable Functions

  Gaoxiang Li, Yu Zhuang

2024-05-20

• Fed-Credit: Robust Federated Learning with Credibility Management

  Jiayan Chen, Zhirong Qian, Tianhui Meng, Xitong Gao, Tian Wang, Weijia Jia

• Robust Deep Reinforcement Learning with Adaptive Adversarial Perturbations in Action Space

  Qianmei Liu, Yufei Kuang, Jie Wang

• Adaptive Batch Normalization Networks for Adversarial Robustness

  Shao-Yuan Lo, Vishal M. Patel

• Adversarially Diversified Rehearsal Memory (ADRM): Mitigating Memory Overfitting Challenge in Continual Learning

  Hikmat Khan, Ghulam Rasool, Nidhal Carla Bouaynaya

• Data Contamination Calibration for Black-box LLMs

  Wentao Ye, Jiaqi Hu, Liyao Li, Haobo Wang, Gang Chen, Junbo Zhao

• Decentralized Privacy Preservation for Critical Connections in Graphs

  Conggai Li, Wei Ni, Ming Ding, Youyang Qu, Jianjun Chen, David Smith, Wenjie Zhang, Thierry Rakotoarivelo

• GAN-GRID: A Novel Generative Attack on Smart Grid Stability Prediction

  Emad Efatinasab, Alessandro Brighente, Mirco Rampazzo, Nahal Azadi, Mauro Conti

• Adaptive Batch Normalization Networks for Adversarial Robustness

  Shao-Yuan Lo, Vishal M. Patel

• Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks

  Marcin Podhajski, Jan Dubiński, Franziska Boenisch, Adam Dziedzic, Agnieszka Pregowska, Tomasz Michalak

• Lockpicking LLMs: A Logit-Based Jailbreak Using Token-level Manipulation

  Yuxi Li, Yi Liu, Yuekang Li, Ling Shi, Gelei Deng, Shengquan Chen, Kailong Wang

2024-05-19

• An Invisible Backdoor Attack Based On Semantic Feature

  Yangming Chen

• Searching Realistic-Looking Adversarial Objects For Autonomous Driving Systems

  Shengxiang Sun, Shenzhe Zhu

• A Constraint-Enforcing Reward for Adversarial Attacks on Text Classifiers

  Tom Roth, Inigo Jauregi Unanue, Alsharif Abuadbba, Massimo Piccardi

• On Robust Reinforcement Learning with Lipschitz-Bounded Policy Networks

  Nicholas H. Barbara, Ruigang Wang, Ian R. Manchester

• Certified Robust Accuracy of Neural Networks Are Bounded due to Bayes Errors

  Ruihan Zhang, Jun Sun

• A GAN-Based Data Poisoning Attack Against Federated Learning Systems and Its Countermeasure

  Wei Sun, Bo Gao, Ke Xiong, Yuwei Wang, Pingyi Fan, Khaled Ben Letaief

• Sketches-based join size estimation under local differential privacy

  Meifan Zhang, Xin Liu, Lihua Yin

• BOSC: A Backdoor-based Framework for Open Set Synthetic Image Attribution

  Jun Wang, Benedetta Tondi, Mauro Barni

2024-05-18

• Revisiting the Robust Generalization of Adversarial Prompt Tuning

  Fan Yang, Mingxuan Xia, Sangzhou Xia, Chicheng Ma, Hui Hui

• Trustworthy Actionable Perturbations

  Jesse Friedbaum, Sudarshan Adiga, Ravi Tandon

• Towards Robust Policy: Enhancing Offline Reinforcement Learning with Adversarial Attacks and Defenses

  Thanh Nguyen, Tung M. Luu, Tri Ton, Chang D. Yoo

• SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks

  Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn

• BadActs: A Universal Backdoor Defense in the Activation Space

  Biao Yi, Sishuo Chen, Yiming Li, Tong Li, Baolei Zhang, Zheli Liu

• UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers

  Duo Peng, Qiuhong Ke, Jun Liu

AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA

Weitao Feng, Wenbo Zhou, Jiyan He, Jie Zhang, Tianyi Wei, Guanlin Li, Tianwei Zhang, Weiming Zhang, Nenghai Yu

• Few-Shot API Attack Detection: Overcoming Data Scarcity with GAN-Inspired Learning

  Udi Aharon, Revital Marbel, Ran Dubin, Amit Dvir, Chen Hajaj

• Detecting Complex Multi-step Attacks with Explainable Graph Neural Network

  Wei Liu, Peng Gao, Haotian Zhang, Ke Li, Weiyong Yang, Xingshen Wei, Shuji Wu

• MediCLIP: Adapting CLIP for Few-shot Medical Image Anomaly Detection

  Ximiao Zhang, Min Xu, Dehui Qiu, Ruixin Yan, Ning Lang, Xiuzhuang Zhou

2024-05-17

• Safeguarding Vision-Language Models Against Patched Visual Prompt Injectors

  Jiachen Sun, Changsheng Wang, Jiongxiao Wang, Yiwei Zhang, Chaowei Xiao

• Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers

  Sheng Yang, Jiawang Bai, Kuofeng Gao, Yong Yang, Yiming Li, Shu-tao Xia

• Multicenter Privacy-Preserving Model Training for Deep Learning Brain Metastases Autosegmentation

  Yixing Huang, Zahra Khodabakhshi, Ahmed Gomaa, Manuel Schmidt, Rainer Fietkau, Matthias Guckenberger, Nicolaus Andratschke, Christoph Bert, Stephanie Tanadini-Lang, Florian Putz

• Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective

  Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang

• Boosting Few-Pixel Robustness Verification via Covering Verification Designs

  Yuval Shapira, Naor Wiesel, Shahar Shabelman, Dana Drachsler-Cohen

• Generative AI for Secure and Privacy-Preserving Mobile Crowdsensing

  Yaoqi Yang, Bangning Zhang, Daoxing Guo, Hongyang Du, Zehui Xiong, Dusit Niyato, Zhu Han

2024-05-16

• Box-Free Model Watermarks Are Prone to Black-Box Removal Attacks

  Haonan An, Guang Hua, Zhiping Lin, Yuguang Fang

• DiffAM: Diffusion-based Adversarial Makeup Transfer for Facial Privacy Protection

  Yuhao Sun, Lingyun Yu, Hongtao Xie, Jiaming Li, Yongdong Zhang

• Keep It Private: Unsupervised Privatization of Online Text

  Calvin Bao, Marine Carpuat

• SecureLLM: Using Compositionality to Build Provably Secure Language Models for Private, Sensitive, and Secret Data

  Abdulrahman Alabdulakreem, Christian M Arnold, Yerim Lee, Pieter M Feenstra, Boris Katz, Andrei Barbu

• Infrared Adversarial Car Stickers

  Xiaopei Zhu, Yuqiu Liu, Zhanhao Hu, Jianmin Li, Xiaolin Hu

• Adversarial Robustness for Visual Grounding of Multimodal Large Language Models

  Kuofeng Gao, Yang Bai, Jiawang Bai, Yong Yang, Shu-Tao Xia

• IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency

  Linshan Hou, Ruili Feng, Zhongyun Hua, Wei Luo, Leo Yu Zhang, Yiming Li

• Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution

  Eslam Zaher, Maciej Trzaskowski, Quan Nguyen, Fred Roosta

• Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy

  Yichuan Shi, Olivera Kotevska, Viktor Reshniak, Abhishek Singh, Ramesh Raskar

• Adversarial Robustness Guarantees for Quantum Classifiers

  Neil Dowling, Maxwell T. West, Angus Southwell, Azar C. Nakhl, Martin Sevior, Muhammad Usman, Kavan Modi

• Learnable Privacy Neurons Localization in Language Models

  Ruizhe Chen, Tianxiang Hu, Yang Feng, Zuozhu Liu

• "What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation

  Meenatchi Sundaram Muthu Selva Annamalai, Georgi Ganev, Emiliano De Cristofaro

2024-05-15

• Identity Overlap Between Face Recognition Train/Test Data: Causing Optimistic Bias in Accuracy Measurement

  Haiyu Wu, Sicong Tian, Jacob Gutierrez, Aman Bhatta, Kağan Öztürk, Kevin W. Bowyer

• Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization

  Kai Hu, Weichen Yu, Tianjun Yao, Xiang Li, Wenhe Liu, Lijun Yu, Yining Li, Kai Chen, Zhiqiang Shen, Matt Fredrikson

• Cross-Input Certified Training for Universal Perturbations

  Changming Xu, Gagandeep Singh

• Towards Evaluating the Robustness of Automatic Speech Recognition Systems via Audio Style Transfer

  Weifei Jin, Yuxin Cao, Junjie Su, Qi Shen, Kai Ye, Derui Wang, Jie Hao, Ziyao Liu

• Words Blending Boxes. Obfuscating Queries in Information Retrieval using Differential Privacy

  Francesco Luigi De Faveri, Guglielmo Faggioli, Nicola Ferro

• Training Deep Learning Models with Hybrid Datasets for Robust Automatic Target Detection on real SAR images

  Benjamin Camus, Théo Voillemin, Corentin Le Barbu, Jean-Christophe Louvigné, Carole Belloni, Emmanuel Vallée

• Properties that allow or prohibit transferability of adversarial attacks among quantized networks

  Abhishek Shrestha, Jürgen Großmann

• DP-RuL: Differentially-Private Rule Learning for Clinical Decision Support Systems

  Josephine Lamp, Lu Feng, David Evans

• Benchmark Early and Red Team Often: A Framework for Assessing and Managing Dual-Use Hazards of AI Foundation Models

  Anthony M. Barrett, Krystal Jackson, Evan R. Murphy, Nada Madkour, Jessica Newman

2024-05-14

• Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring

  Khoi Tran Dang, Kevin Delmas, Jérémie Guiochet, Joris Guérin

• Towards Safe Large Language Models for Medicine

  Tessa Han, Aounon Kumar, Chirag Agarwal, Himabindu Lakkaraju

• SpeechGuard: Exploring the Adversarial Robustness of Multimodal Large Language Models

  Raghuveer Peri, Sai Muralidhar Jayanthi, Srikanth Ronanki, Anshu Bhatia, Karel Mundnich, Saket Dingliwal, Nilaksh Das, Zejiang Hou, Goeric Huybrechts, Srikanth Vishnubhotla, Daniel Garcia-Romero, Sundararajan Srinivasan, Kyu J Han, Katrin Kirchhoff

• UnMarker: A Universal Attack on Defensive Watermarking

  Andre Kassis, Urs Hengartner

• Certifying Robustness of Graph Convolutional Networks for Node Perturbation with Polyhedra Abstract Interpretation

  Boqi Chen, Kristóf Marussy, Oszkár Semeráth, Gunter Mussbacher, Dániel Varró

• Differentially Private Federated Learning: A Systematic Review

  Jie Fu, Yuan Hong, Xinpeng Ling, Leixia Wang, Xun Ran, Zhiyu Sun, Wendy Hui Wang, Zhili Chen, Yang Cao

• Work-in-Progress: Crash Course: Can (Under Attack) Autonomous Driving Beat Human Drivers?

  Francesco Marchiori, Alessandro Brighente, Mauro Conti

• Adversarial Machine Learning Threats to Spacecraft

  Rajiv Thummala, Shristi Sharma, Matteo Calabrese, Gregory Falco

• Neural Collapse Meets Differential Privacy: Curious Behaviors of NoisyGD with Near-perfect Representation Learning

  Chendi Wang, Yuqing Zhu, Weijie J. Su, Yu-Xiang Wang

• The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks

  Ziquan Liu, Yufei Cui, Yan Yan, Yi Xu, Xiangyang Ji, Xue Liu, Antoni B. Chan

• RS-Reg: Probabilistic and Robust Certified Regression Through Randomized Smoothing

  Aref Miri Rekavandi, Olga Ohrimenko, Benjamin I.P. Rubinstein

• Private Data Leakage in Federated Human Activity Recognition for Wearable Healthcare Devices

  Kongyang Chen, Dongping Zhang, Bing Mi

2024-05-13

• GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation

  Andrey V. Galichin, Mikhail Pautov, Alexey Zhavoronkin, Oleg Y. Rogov, Ivan Oseledets

• Environmental Matching Attack Against Unmanned Aerial Vehicles Object Detection

  Dehong Kong, Siyuan Liang, Wenqi Ren

• CrossCert: A Cross-Checking Detection Approach to Patch Robustness Certification for Deep Learning Models

  Qilin Zhou, Zhengyuan Wei, Haipeng Wang, Bo Jiang, W.K. Chan

• RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors

  Liam Dugan, Alyssa Hwang, Filip Trhlik, Josh Magnus Ludan, Andrew Zhu, Hainiu Xu, Daphne Ippolito, Chris Callison-Burch

• Backdoor Removal for Generative Large Language Models

  Haoran Li, Yulin Chen, Zihao Zheng, Qi Hu, Chunkit Chan, Heshan Liu, Yangqiu Song

• Evaluating Google's Protected Audience Protocol

  Minjun Long, David Evans

2024-05-12

• VALID: a Validated Algorithm for Learning in Decentralized Networks with Possible Adversarial Presence

  Mayank Bakshi, Sara Ghasvarianjahromi, Yauhen Yakimenka, Allison Beemer, Oliver Kosut, Joerg Kliewer

2024-05-11

• Shadow-Free Membership Inference Attacks: Recommender Systems Are More Vulnerable Than You Thought

  Xiaoxiao Chi, Xuyun Zhang, Yan Wang, Lianyong Qi, Amin Beheshti, Xiaolong Xu, Kim-Kwang Raymond Choo, Shuo Wang, Hongsheng Hu

• Disrupting Style Mimicry Attacks on Video Imagery

  Josephine Passananti, Stanley Wu, Shawn Shan, Haitao Zheng, Ben Y. Zhao

2024-05-10

• Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems

  David "davidad" Dalrymple, Joar Skalse, Yoshua Bengio, Stuart Russell, Max Tegmark, Sanjit Seshia, Steve Omohundro, Christian Szegedy, Ben Goldhaber, Nora Ammann, Alessandro Abate, Joe Halpern, Clark Barrett, Ding Zhao, Tan Zhi-Xuan, Jeannette Wing, Joshua Tenenbaum

• Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning

  Yujie Zhang, Neil Gong, Michael K. Reiter

• Disttack: Graph Adversarial Attacks Toward Distributed GNN Training

  Yuxiang Zhang, Xin Liu, Meng Wu, Wei Yan, Mingyu Yan, Xiaochun Ye, Dongrui Fan

• Exploring the Interplay of Interpretability and Robustness in Deep Neural Networks: A Saliency-guided Approach

  Amira Guesmi, Nishant Suresh Aswani, Muhammad Shafique

• Improving Transferable Targeted Adversarial Attack via Normalized Logit Calibration and Truncated Feature Mixing

  Juanjuan Weng, Zhiming Luo, Shaozi Li

• Evaluating Adversarial Robustness in the Spatial Frequency Domain

  Keng-Hsin Liao, Chin-Yuan Yeh, Hsi-Wen Chen, Ming-Syan Chen

• Certified $\ell_2$ Attribution Robustness via Uniformly Smoothed Attributions

  Fan Wang, Adams Wai-Kin Kong

• Risks of Practicing Large Language Models in Smart Grid: Threat Modeling and Validation

  Jiangnan Li, Yingyuan Yang, Jinyuan Sun

• PLeak: Prompt Leaking Attacks against Large Language Model Applications

  Bo Hui, Haolin Yuan, Neil Gong, Philippe Burlina, Yinzhi Cao

• LLM-Generated Black-box Explanations Can Be Adversarially Helpful

  Rohan Ajwani, Shashidhar Reddy Javaji, Frank Rudzicz, Zining Zhu

2024-05-09

• Towards Robust Physical-world Backdoor Attacks on Lane Detection

  Xinwei Zhang, Aishan Liu, Tianyuan Zhang, Siyuan Liang, Xianglong Liu

• Trustworthy AI-Generative Content in Intelligent 6G Network: Adversarial, Privacy, and Fairness

  Siyuan Li, Xi Lin, Yaju Liu, Jianhua Li

• Chain of Attack: a Semantic-Driven Contextual Multi-Turn attacker for LLM

  Xikang Yang, Xuehai Tang, Songlin Hu, Jizhong Han

• Towards Accurate and Robust Architectures via Neural Architecture Search

  Yuwei Ou, Yuqi Feng, Yanan Sun

• Universal Adversarial Perturbations for Vision-Language Pre-trained Models

  Peng-Fei Zhang, Zi Huang, Guangdong Bai

• Poisoning-based Backdoor Attacks for Arbitrary Target Label with Positive Triggers

  Binxiao Huang, Jason Chun Lok, Chang Liu, Ngai Wong

• Model Inversion Robustness: Can Transfer Learning Help?

  Sy-Tuyen Ho, Koh Jun Hao, Keshigeyan Chandrasegaran, Ngoc-Bao Nguyen, Ngai-Man Cheung

• Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems

  Amin Aminifar, Matin Shokri, Amir Aminifar

• Link Stealing Attacks Against Inductive Graph Neural Networks

  Yixin Wu, Xinlei He, Pascal Berrang, Mathias Humbert, Michael Backes, Neil Zhenqiang Gong, Yang Zhang

• A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data

  Meenatchi Sundaram Muthu Selva Annamalai, Andrea Gadotti, Luc Rocher

• High-Performance Privacy-Preserving Matrix Completion for Trajectory Recovery

  Jiahao Guo, An-Bao Xu

• Special Characters Attack: Toward Scalable Training Data Extraction From Large Language Models

  Yang Bai, Ge Pei, Jindong Gu, Yong Yang, Xingjun Ma

• Muting Whisper: A Universal Acoustic Adversarial Attack on Speech Foundation Models

  Vyas Raina, Rao Ma, Charles McGhee, Kate Knill, Mark Gales

• BB-Patch: BlackBox Adversarial Patch-Attack using Zeroth-Order Optimization

  Satyadwyoom Kumar, Saurabh Gupta, Arun Balaji Buduru

• Hard Work Does Not Always Pay Off: Poisoning Attacks on Neural Architecture Search

  Zachary Coalson, Huazheng Wang, Qingyun Wu, Sanghyun Hong

2024-05-08

• Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution

  Shuo Shao, Yiming Li, Hongwei Yao, Yiling He, Zhan Qin, Kui Ren

• The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audio

  Yuankun Xie, Yi Lu, Ruibo Fu, Zhengqi Wen, Zhiyong Wang, Jianhua Tao, Xin Qi, Xiaopeng Wang, Yukun Liu, Haonan Cheng, Long Ye, Yi Sun

• BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language Models

  Chu Fei Luo, Ahmad Ghawanmeh, Xiaodan Zhu, Faiza Khan Khattak

• Mitigating Bias Using Model-Agnostic Data Attribution

  Sander De Coninck, Wei-Cheng Wang, Sam Leroux, Pieter Simoens

• Espresso: Robust Concept Filtering in Text-to-Image Models

  Anudeep Das, Vasisht Duddu, Rui Zhang, N. Asokan

• Towards Efficient Training and Evaluation of Robust Models against $l_0$ Bounded Adversarial Perturbations

  Xuyang Zhong, Yixiao Huang, Chen Liu

• Adversarial Threats to Automatic Modulation Open Set Recognition in Wireless Networks

  Yandie Yang, Sicheng Zhang, Kuixian Li, Qiao Tian, Yun Lin

• HackCar: a test platform for attacks and defenses on a cost-contained automotive architecture

  Dario Stabili, Filip Valgimigli, Edoardo Torrini, Mirco Marchetti

• Systematic Use of Random Self-Reducibility against Physical Attacks

  Ferhat Erata, TingHung Chiu, Anthony Etim, Srilalith Nampally, Tejas Raju, Rajashree Ramu, Ruzica Piskac, Timos Antonopoulos, Wenjie Xiong, Jakub Szefer

• Poser: Unmasking Alignment Faking LLMs by Manipulating Their Internals

  Joshua Clymer, Caden Juang, Severin Field

• Adversary-Guided Motion Retargeting for Skeleton Anonymization

  Thomas Carr, Depeng Xu, Aidong Lu

• Model Reconstruction Using Counterfactual Explanations: Mitigating the Decision Boundary Shift

  Pasan Dissanayake, Sanghamitra Dutta

• Untargeted Adversarial Attack on Knowledge Graph Embeddings

  Tianzhe Zhao, Jiaoyan Chen, Yanchi Ru, Qika Lin, Yuxia Geng, Jun Liu

2024-05-07

• Enhancing Scalability of Metric Differential Privacy via Secret Dataset Partitioning and Benders Decomposition

  Chenxi Qiu

• Locally Differentially Private In-Context Learning

  Chunyan Zheng, Keke Sun, Wenhao Zhao, Haibo Zhou, Lixin Jiang, Shaoyang Song, Chunlai Zhou

• A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model

  Tianxiu Xie, Keke Gai, Jing Yu, Liehuang Zhu, Kim-Kwang Raymond Choo

• Revisiting character-level adversarial attacks

  Elias Abad Rocamora, Yongtao Wu, Fanghui Liu, Grigorios G. Chrysos, Volkan Cevher

• IPFed: Identity protected federated learning for user authentication

  Yosuke Kaga, Yusei Suzuki, Kenta Takahashi

• Exposing AI-generated Videos: A Benchmark Dataset and a Local-and-Global Temporal Defect Based Detection Method

  Peisong He, Leyao Zhu, Jiaxing Li, Shiqi Wang, Haoliang Li

• Breast Histopathology Image Retrieval by Attention-based Adversarially Regularized Variational Graph Autoencoder with Contrastive Learning-Based Feature Extraction

  Nematollah Saeidi, Hossein Karshenas, Bijan Shoushtarian, Sepideh Hatamikia, Ramona Woitek, Amirreza Mahbod

• Effective and Robust Adversarial Training against Data and Label Corruptions

  Peng-Fei Zhang, Zi Huang, Xin-Shun Xu, Guangdong Bai

• Unlearning Backdoor Attacks through Gradient-Based Model Pruning

  Kealan Dunnett, Reza Arablouei, Dimity Miller, Volkan Dedeoglu, Raja Jurdak

• Explainability-Informed Targeted Malware Misclassification

  Quincy Card, Kshitiz Aryal, Maanak Gupta

• Enabling Privacy-Preserving and Publicly Auditable Federated Learning

  Huang Zeng, Anjia Yang, Jian Weng, Min-Rong Chen, Fengjun Xiao, Yi Liu, Ye Yao

• A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning

  Xiaoyang Xu, Mengda Yang, Wenzhe Yi, Ziang Li, Juan Wang, Hongxin Hu, Yong Zhuang, Yaxin Liu

2024-05-06

• To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models

  George-Octavian Barbulescu, Peter Triantafillou

• Assessing Adversarial Robustness of Large Language Models: An Empirical Study

  Zeyu Yang, Zhao Meng, Xiaochen Zheng, Roger Wattenhofer

• Exploring Frequencies via Feature Mixing and Meta-Learning for Improving Adversarial Transferability

  Juanjuan Weng, Zhiming Luo, Shaozi Li

• UnsafeBench: Benchmarking Image Safety Classifiers on Real-World and AI-Generated Images

  Yiting Qu, Xinyue Shen, Yixin Wu, Michael Backes, Savvas Zannettou, Yang Zhang

• Learning Robust Classifiers with Self-Guided Spurious Correlation Mitigation

  Guangtao Zheng, Wenqian Ye, Aidong Zhang

• Provably Unlearnable Examples

  Derui Wang, Minhui Xue, Bo Li, Seyit Camtepe, Liming Zhu

• GI-SMN: Gradient Inversion Attack against Federated Learning without Prior Knowledge

  Jin Qian, Kaimin Wei, Yongdong Wu, Jilian Zhang, Jipeng Chen, Huan Bao

• Federated Learning Privacy: Attacks, Defenses, Applications, and Policy Landscape - A Survey

  Joshua C. Zhao, Saurabh Bagchi, Salman Avestimehr, Kevin S. Chan, Somali Chaterji, Dimitris Dimitriadis, Jiacheng Li, Ninghui Li, Arash Nourian, Holger R. Roth

• Cutting through buggy adversarial example defenses: fixing 1 line of code breaks Sabre

  Nicholas Carlini

• FOBNN: Fast Oblivious Binarized Neural Network Inference

  Xin Chen, Zhili Chen, Benchang Dong, Shiwen Wei, Lin Chen, Daojing He

• DarkFed: A Data-Free Backdoor Attack in Federated Learning

  Minghui Li, Wei Wan, Yuxuan Ning, Shengshan Hu, Lulu Xue, Leo Yu Zhang, Yichen Wang

• LaserEscape: Detecting and Mitigating Optical Probing Attacks

  Saleh Khalaj Monfared, Kyle Mitard, Andrew Cannon, Domenic Forte, Shahin Tajik

• Is ReLU Adversarially Robust?

  Korn Sooksatra, Greg Hamerly, Pablo Rivas

• On Adversarial Examples for Text Classification by Perturbing Latent Representations

  Korn Sooksatra, Bikram Khanal, Pablo Rivas

• Enhancing O-RAN Security: Evasion Attacks and Robust Defenses for Graph Reinforcement Learning-based Connection Management

  Ravikumar Balakrishnan, Marius Arvinte, Nageen Himayat, Hosein Nikopour, Hassnaa Moustafa

• Is ReLU Adversarially Robust?

  Korn Sooksatra, Greg Hamerly, Pablo Rivas

• On Adversarial Examples for Text Classification by Perturbing Latent Representations

  Korn Sooksatra, Bikram Khanal, Pablo Rivas

• Enhancing O-RAN Security: Evasion Attacks and Robust Defenses for Graph Reinforcement Learning-based Connection Management

  Ravikumar Balakrishnan, Marius Arvinte, Nageen Himayat, Hosein Nikopour, Hassnaa Moustafa

• Generative adversarial learning with optimal input dimension and its adaptive generator architecture

  Zhiyao Tan, Ling Zhou, Huazhen Lin

• Secure Inference for Vertically Partitioned Data Using Multiparty Homomorphic Encryption

  Shuangyi Chen, Yue Ju, Zhongwen Zhu, Ashish Khisti

• Differentially Private Federated Learning without Noise Addition: When is it Possible?

  Jiang Zhang, Yahya H Ezzeldin, Ahmed Roushdy Elkordy, Konstantinos Psounis, Salman Avestimehr

• Differentially Private Synthetic Data with Private Density Estimation

  Nikolija Bojkovic, Po-Ling Loh

2024-05-05

• Safe Reinforcement Learning with Learned Non-Markovian Safety Constraints

  Siow Meng Low, Akshat Kumar

• AnoGAN for Tabular Data: A Novel Approach to Anomaly Detection

  Aditya Singh, Pavan Reddy

• Confidential and Protected Disease Classifier using Fully Homomorphic Encryption

  Aditya Malik, Nalini Ratha, Bharat Yalavarthi, Tilak Sharma, Arjun Kaushik, Charanjit Jutla

• Trojans in Large Language Models of Code: A Critical Review through a Trigger-Based Taxonomy

  Aftab Hussain, Md Rafiqul Islam Rabin, Toufique Ahmed, Bowen Xu, Premkumar Devanbu, Mohammad Amin Alipour

• Defense against Joint Poison and Evasion Attacks: A Case Study of DERMS

  Zain ul Abdeen, Padmaksha Roy, Ahmad Al-Tawaha, Rouxi Jia, Laura Freeman, Peter Beling, Chen-Ching Liu, Alberto Sangiovanni-Vincentelli, Ming Jin

2024-05-04

• Leveraging the Human Ventral Visual Stream to Improve Neural Network Robustness

  Zhenan Shao, Linjian Ma, Bo Li, Diane M. Beck

• Detecting Edited Knowledge in Language Models

  Paul Youssef, Zhixue Zhao, Jörg Schlötterer, Christin Seifert

• Can LLMs Deeply Detect Complex Malicious Queries? A Framework for Jailbreaking via Obfuscating Intent

  Shang Shang, Xinqiang Zhao, Zhongjiang Yao, Yepeng Yao, Liya Su, Zijing Fan, Xiaodan Zhang, Zhengwei Jiang

• PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds

  Zehan Zhu, Yan Huang, Xin Wang, Jinming Xu

• Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples

  Matous Kozak, Luca Demetrio, Dmitrijs Trizna, Fabio Roli

• Metric Differential Privacy at the User-Level

  Jacob Imola, Amrita Roy Chowdhury, Kamalika Chaudhuri

• Your Network May Need to Be Rewritten: Network Adversarial Based on High-Dimensional Function Graph Decomposition

  Xiaoyan Su, Yinghao Zhu, Run Li

2024-05-03

• Impact of Architectural Modifications on Deep Learning Adversarial Robustness

  Firuz Juraev, Mohammed Abuhamad, Simon S. Woo, George K Thiruvathukal, Tamer Abuhmed

• From Attack to Defense: Insights into Deep Learning Security Measures in Black-Box Settings

  Firuz Juraev, Mohammed Abuhamad, Eric Chan-Tin, George K. Thiruvathukal, Tamer Abuhmed

• Adversarial Botometer: Adversarial Analysis for Social Bot Detection

  Shaghayegh Najari, Davood Rafiee, Mostafa Salehi, Reza Farahbakhsh

• Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach

  Anton Plaksin, Vitaly Kalev

• Uniformly Stable Algorithms for Adversarial Training and Beyond

  Jiancong Xiao, Jiawei Zhang, Zhi-Quan Luo, Asuman Ozdaglar

• A Novel Approach to Guard from Adversarial Attacks using Stable Diffusion

  Trinath Sai Subhash Reddy Pittala, Uma Maheswara Rao Meleti, Geethakrishna Puligundla

• Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes

  Sang Bin Moon, Abolfazl Hashemi

• ProFLingo: A Fingerprinting-based Copyright Protection Scheme for Large Language Models

  Heng Jin, Chaoyu Zhang, Shanghao Shi, Wenjing Lou, Y. Thomas Hou

• Adaptive and robust watermark against model extraction attack

  Kaiyi Pang, Tao Qi, Chuhan Wu, Minhao Bai

2024-05-02

• PVF (Parameter Vulnerability Factor): A Quantitative Metric Measuring AI Vulnerability and Resilience Against Parameter Corruptions

  Xun Jiao, Fred Lin, Harish D. Dixit, Joel Coburn, Abhinav Pandey, Han Wang, Jianyu Huang, Venkat Ramesh, Wang Xu, Daniel Moore, Sriram Sankar

• Privacy-aware Berrut Approximated Coded Computing for Federated Learning

  Xavier Martínez Luaña, Rebeca P. Díaz Redondo, Manuel Fernández Veiga

• Robust Risk-Sensitive Reinforcement Learning with Conditional Value-at-Risk

  Xinyi Ni, Lifeng Lai

• Adversarial Attacks on Reinforcement Learning Agents for Command and Control

  Ahaan Dabholkar, James Z. Hare, Mark Mittrick, John Richardson, Nicholas Waytowich, Priya Narayanan, Saurabh Bagchi

• ATTAXONOMY: Unpacking Differential Privacy Guarantees Against Practical Adversaries

  Rachel Cummings, Shlomi Hod, Jayshree Sarathy, Marika Swanberg

• Explainability Guided Adversarial Evasion Attacks on Malware Detectors

  Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam, Moustafa Saleh

• Backdoor-based Explainable AI Benchmark for High Fidelity Evaluation of Attribution Methods

  Peiyu Yang, Naveed Akhtar, Jiantong Jiang, Ajmal Mian

• Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy

  Wei-Ning Chen, Berivan Isik, Peter Kairouz, Albert No, Sewoong Oh, Zheng Xu

• Temporal assessment of malicious behaviors: application to turnout field data monitoring

  Sara Abdellaoui, Emil Dumitrescu, Cédric Escudero, Eric Zamaï

2024-05-01

• Robustness of graph embedding methods for community detection

  Zhi-Feng Wei, Pablo Moriano, Ramakrishnan Kannan

• Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing

  Daniel Gibert, Luca Demetrio, Giulio Zizzo, Quan Le, Jordi Planes, Battista Biggio

2024-04-30

• Transferring Troubles: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning

  Xuanli He, Jun Wang, Qiongkai Xu, Pasquale Minervini, Pontus Stenetorp, Benjamin I. P. Rubinstein, Trevor Cohn

• AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples

  Antonio Emanuele Cinà, Jérôme Rony, Maura Pintor, Luca Demetrio, Ambra Demontis, Battista Biggio, Ismail Ben Ayed, Fabio Roli

• ASAM: Boosting Segment Anything Model with Adversarial Tuning

  Bo Li, Haoke Xiao, Lv Tang

• Probing Unlearned Diffusion Models: A Transferable Adversarial Attack Perspective

  Xiaoxuan Han, Songlin Yang, Wei Wang, Yang Li, Jing Dong

• Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective

  Wanqi Zhou, Shuanghao Bai, Qibin Zhao, Badong Chen

2024-04-29

• Do Neutral Prompts Produce Insecure Code? FormAI-v2 Dataset: Labelling Vulnerabilities in Code Generated by Large Language Models

  Norbert Tihanyi, Tamas Bisztray, Mohamed Amine Ferrag, Ridhi Jain, Lucas C. Cordeiro

• Certification of Speaker Recognition Models to Additive Perturbations

  Dmitrii Korzh, Elvir Karimov, Mikhail Pautov, Oleg Y. Rogov, Ivan Oseledets

• Harmonic Machine Learning Models are Robust

  Nicholas S. Kersting, Yi Li, Aman Mohanty, Oyindamola Obisesan, Raphael Okochu

• Uncertainty-boosted Robust Video Activity Anticipation

  Zhaobo Qi, Shuhui Wang, Weigang Zhang, Qingming Huang

• Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots

  Xi Xin, Fei Huang, Giles Hooker

• A Systematic Evaluation of Adversarial Attacks against Speech Emotion Recognition Models

  Nicolas Facchinetti, Federico Simonetta, Stavros Ntalampiras

• Assessing Cybersecurity Vulnerabilities in Code Large Language Models

  Md Imran Hossen, Jianyi Zhang, Yinzhi Cao, Xiali Hei

2024-04-27

• Adversarial Examples: Generation Proposal in the Context of Facial Recognition Systems

  Marina Fuster, Ignacio Vidaurreta

• Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks

  Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström

• Privacy-Preserving Aggregation for Decentralized Learning with Byzantine-Robustness

  Ali Reza Ghavamipour, Benjamin Zi Hao Zhao, Oguzhan Ersoy, Fatih Turkmen

• Are Watermarks Bugs for Deepfake Detectors? Rethinking Proactive Forensics

  Xiaoshuai Wu, Xin Liao, Bo Ou, Yuling Liu, Zheng Qin

• Improving Smart Contract Security with Contrastive Learning-based Vulnerability Detection

  Yizhou Chen, Zeyu Sun, Zhihao Gong, Dan Hao

2024-04-26

• Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs

  Valeriia Cherepanova, James Zou

• Human-Imperceptible Retrieval Poisoning Attacks in LLM-Powered Applications

  Quan Zhang, Binqi Zeng, Chijin Zhou, Gwihwan Go, Heyuan Shi, Yu Jiang

• Enhancing Privacy and Security of Autonomous UAV Navigation

  Vatsal Aggarwal, Arjun Ramesh Kaushik, Charanjit Jutla, Nalini Ratha

• M3BAT: Unsupervised Domain Adaptation for Multimodal Mobile Sensing with Multi-Branch Adversarial Training

  Lakmal Meegahapola, Hamza Hassoune, Daniel Gatica-Perez

• Defending Spiking Neural Networks against Adversarial Attacks through Image Purification

  Weiran Chen, Qi Sun, Qi Xu

• Adversarial Reweighting with $α$-Power Maximization for Domain Adaptation

  Xiang Gu, Xi Yu, Yan Yang, Jian Sun, Zongben Xu

• Estimating the Robustness Radius for Randomized Smoothing with 100$\times$ Sample Efficiency

  Emmanouil Seferis, Stefanos Kollias, Chih-Hong Cheng

• Adversarial Consistency and the Uniqueness of the Adversarial Bayes Classifier

  Natalie S. Frank

• Evaluations of Machine Learning Privacy Defenses are Misleading

  Michael Aerni, Jie Zhang, Florian Tramèr

• Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning

  Tao Liu, Yuhang Zhang, Zhu Feng, Zhiqin Yang, Chen Xu, Dapeng Man, Wu Yang

• Center-Based Relaxed Learning Against Membership Inference Attacks

  Xingli Fang, Jung-Eun Kim

• Efficient Exploration of Image Classifier Failures with Bayesian Optimization and Text-to-Image Models

  Adrien Le Coz, Houssem Ouertatani, Stéphane Herbin, Faouzi Adjed

2024-04-25

• Constructing Optimal Noise Channels for Enhanced Robustness in Quantum Machine Learning

  David Winderl, Nicola Franco, Jeanette Miriam Lorenz

• Towards Precise Observations of Neural Model Robustness in Classification

  Wenchuan Mu, Kwan Hui Lim

• Energy-Latency Manipulation of Multi-modal Large Language Models via Verbose Samples

  Kuofeng Gao, Jindong Gu, Yang Bai, Shu-Tao Xia, Philip Torr, Wei Liu, Zhifeng Li

• Understanding Privacy Risks of Embeddings Induced by Large Language Models

  Zhihao Zhu, Ninglu Shao, Defu Lian, Chenwang Wu, Zheng Liu, Yi Yang, Enhong Chen

• Don't Say No: Jailbreaking LLM by Suppressing Refusal

  Yukai Zhou, Wenjie Wang

• PAD: Patch-Agnostic Defense against Adversarial Patch Attacks

  Lihua Jing, Rui Wang, Wenqi Ren, Xin Dong, Cong Zou

• Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference

  Zhe Zhang, Ryumei Nakada, Linjun Zhang

• Boosting Model Resilience via Implicit Adversarial Data Augmentation

  Xiaoling Zhou, Wei Ye, Zhemg Lee, Rui Xie, Shikun Zhang

• Generating Minimalist Adversarial Perturbations to Test Object-Detection Models: An Adaptive Multi-Metric Evolutionary Search Approach

  Cristopher McIntyre-Garcia, Adrien Heymans, Beril Borali, Won-Sook Lee, Shiva Nejati

• A Notion of Uniqueness for the Adversarial Bayes Classifier

  Natalie S. Frank

2024-04-24

• A General Black-box Adversarial Attack on Graph-based Fake News Detectors

  Peican Zhu, Zechen Pan, Yang Liu, Jiwei Tian, Keke Tang, Zhen Wang

• Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks

  Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung, Che-Rung Lee

• Universal Adversarial Triggers Are Not Universal

  Nicholas Meade, Arkil Patel, Siva Reddy

• 3D Face Morphing Attack Generation using Non-Rigid Registration

  Jag Mohan Singh, Raghavendra Ramachandra

• Vision Transformer-based Adversarial Domain Adaptation

  Yahan Li, Yuan Wu

• Beyond Deepfake Images: Detecting AI-Generated Videos

  Danial Samadi Vahdati, Tai D. Nguyen, Aref Azizpour, Matthew C. Stamm

• MISLEAD: Manipulating Importance of Selected features for Learning Epsilon in Evasion Attack Deception

  Vidit Khazanchi, Pavan Kulkarni, Yuvaraj Govindarajulu, Manojkumar Parmar

• CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning

  Haolin Wu, Jing Chen, Ruiying Du, Cong Wu, Kun He, Xingcan Shang, Hao Ren, Guowen Xu

• Security Analysis of WiFi-based Sensing Systems: Threats from Perturbation Attacks

  Hangcheng Cao, Wenbin Huang, Guowen Xu, Xianhao Chen, Ziyang He, Jingyang Hu, Hongbo Jiang, Yuguang Fang

• PoisonedFL: Model Poisoning Attacks to Federated Learning via Multi-Round Consistency

  Yueqi Xie, Minghong Fang, Neil Zhenqiang Gong

• Noise Variance Optimization in Differential Privacy: A Game-Theoretic Approach Through Per-Instance Differential Privacy

  Sehyun Ryu, Jonggyu Jang, Hyun Jong Yang

• Advancing Recommender Systems by mitigating Shilling attacks

  Aditya Chichani, Juzer Golwala, Tejas Gundecha, Kiran Gawande

• Investigating the prompt leakage effect and black-box defenses for multi-turn LLM interactions

  Divyansh Agarwal, Alexander R. Fabbri, Philippe Laban, Shafiq Joty, Caiming Xiong, Chien-Sheng Wu

• An Analysis of Recent Advances in Deepfake Image Detection in an Evolving Threat Landscape

  Sifat Muhammad Abdullah, Aravind Cheruvu, Shravya Kanchi, Taejoong Chung, Peng Gao, Murtuza Jadliwala, Bimal Viswanath

• Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption

  Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross, Vishnu Boddeti, Nalini Ratha

• A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models

  Maximilian Wendlinger, Kilian Tscharke, Pascal Debus

• Attacks on Third-Party APIs of Large Language Models

  Wanru Zhao, Vidit Khazanchi, Haodi Xing, Xuanli He, Qiongkai Xu, Nicholas Donald Lane

2024-04-23

• Talk Too Much: Poisoning Large Language Models under Token Limit

  Jiaming He, Wenbo Jiang, Guanyu Hou, Wenshu Fan, Rui Zhang, Hongwei Li

• A Customer Level Fraudulent Activity Detection Benchmark for Enhancing Machine Learning Model Research and Evaluation

  Phoebe Jing, Yijing Gao, Xianlong Zeng

• Leverage Variational Graph Representation For Model Poisoning on Federated Learning

  Kai Li, Xin Yuan, Jingjing Zheng, Wei Ni, Falko Dressler, Abbas Jamalipour

• Formal Verification of Graph Convolutional Networks with Uncertain Node Features and Uncertain Graph Structure

  Tobias Ladner, Michael Eichelbeck, Matthias Althoff

• Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures

  Thanh Toan Nguyen, Quoc Viet Hung Nguyen, Thanh Tam Nguyen, Thanh Trung Huynh, Thanh Thi Nguyen, Matthias Weidlich, Hongzhi Yin

• Double Privacy Guard: Robust Traceable Adversarial Watermarking against Face Recognition

  Yunming Zhang, Dengpan Ye, Sipeng Shen, Caiyun Xie, Ziyi Liu, Jiacheng Deng, Long Tang

• Every Breath You Don't Take: Deepfake Speech Detection Using Breath

  Seth Layton, Thiago De Andrade, Daniel Olszewski, Kevin Warren, Carrie Gates, Kevin Butler, Patrick Traynor

• Rethinking LLM Memorization through the Lens of Adversarial Compression

  Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter

• Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs

  Javier Rando, Francesco Croce, Kryštof Mitka, Stepan Shabalin, Maksym Andriushchenko, Nicolas Flammarion, Florian Tramèr

• The Adversarial AI-Art: Understanding, Generation, Detection, and Benchmarking

  Yuying Li, Zeyan Liu, Junyi Zhao, Liangqin Ren, Fengjun Li, Jiebo Luo, Bo Luo

• Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares

  Gavin Brown, Jonathan Hayase, Samuel Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith

2024-04-22

• Protecting Your LLMs with Information Bottleneck

  Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian

• Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback

  Wenyi Xiao, Ziwei Huang, Leilei Gan, Wanggui He, Haoyuan Li, Zhelun Yu, Hao Jiang, Fei Wu, Linchao Zhu

• Typos that Broke the RAG's Back: Genetic Attack on RAG Pipeline by Simulating Documents in the Wild via Low-level Perturbations

  Sukmin Cho, Soyeong Jeong, Jeongyeon Seo, Taeho Hwang, Jong C. Park

• Zero-shot Cross-lingual Stance Detection via Adversarial Language Adaptation

  Bharathi A, Arkaitz Zubiaga

• Swap It Like Its Hot: Segmentation-based spoof attacks on eye-tracking images

  Anish S. Narkar, Brendan David-John

• FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge

  Hanzhe Li, Jiaran Zhou, Bin Li, Junyu Dong, Yuezun Li

• CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction

  Wenhao Lan, Yijun Yang, Haihua Shen, Shan Li

• Towards Better Adversarial Purification via Adversarial Denoising Diffusion Training

  Yiming Liu, Kezhao Liu, Yao Xiao, Ziyi Dong, Xiaogang Xu, Pengxu Wei, Liang Lin

• Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference

  Yujin Han, Difan Zou

• Distributional Black-Box Model Inversion Attack with Multi-Agent Reinforcement Learning

  Huan Bao, Kaimin Wei, Yongdong Wu, Jin Qian, Robert H. Deng

• Explicit Lipschitz Value Estimation Enhances Policy Robustness Against Perturbation

  Xulin Chen, Ruipeng Liu, Garrett E. Katz

• Dual Model Replacement:invisible Multi-target Backdoor Attack based on Federal Learning

  Rong Wang, Guichen Zhou, Mingjun Gao, Yunpeng Xiao

• Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction

  Zifan Zhang, Minghong Fang, Jiayuan Huang, Yuchen Liu

• A mean curvature flow arising in adversarial training

  Leon Bungert, Tim Laux, Kerrek Stinson

• Offensive AI: Enhancing Directory Brute-forcing Attack with the Use of Language Models

  Alberto Castagnaro, Mauro Conti, Luca Pajola

2024-04-21

• Reliable Model Watermarking: Defending Against Theft without Compromising on Evasion

  Hongyu Zhu, Sichu Liang, Wentao Hu, Fangqi Li, Ju Jia, Shilin Wang

• FedMPQ: Secure and Communication-Efficient Federated Learning with Multi-codebook Product Quantization

  Xu Yang, Jiapeng Zhang, Qifeng Zhang, Zhuo Tang

• Interval Abstractions for Robust Counterfactual Explanations

  Junqi Jiang, Francesco Leofante, Antonio Rago, Francesca Toni

• Towards General Conceptual Model Editing via Adversarial Representation Engineering

  Yihao Zhang, Zeming Wei, Jun Sun, Meng Sun

• Trojan Detection in Large Language Models: Insights from The Trojan Detection Challenge

  Narek Maloyan, Ekansh Verma, Bulat Nutfullin, Bislan Ashinov

• Attack on Scene Flow using Point Clouds

  Haniyeh Ehsani Oskouie, Mohammad-Shahram Moin, Shohreh Kasaei

• Mean Aggregator Is More Robust Than Robust Aggregators Under Label Poisoning Attacks

  Jie Peng, Weiyu Li, Qing Ling

• LLMs in Web-Development: Evaluating LLM-Generated PHP code unveiling vulnerabilities and limitations

  Rebeka Tóth, Tamas Bisztray, László Erdodi

• Robust EEG-based Emotion Recognition Using an Inception and Two-sided Perturbation Model

  Shadi Sartipi, Mujdat Cetin

• AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs

  Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian

2024-04-20

• Pixel is a Barrier: Diffusion Models Are More Adversarially Robust Than We Think

  Haotian Xue, Yongxin Chen

• AdvLoRA: Adversarial Low-Rank Adaptation of Vision-Language Models

  Yuheng Ji, Yue Liu, Zhicheng Zhang, Zhao Zhang, Yuting Zhao, Gang Zhou, Xingwei Zhang, Xinwang Liu, Xiaolong Zheng

• PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud

  Zhepeng Wang, Yi Sheng, Nirajan Koirala, Kanad Basu, Taeho Jung, Cheng-Chang Lu, Weiwen Jiang

• Beyond Score Changes: Adversarial Attack on No-Reference Image Quality Assessment from Two Perspectives

  Chenxi Yang, Yujia Liu, Dingquan Li, Yan Zhong, Tingting Jiang

• Backdoor Attacks and Defenses on Semantic-Symbol Reconstruction in Semantic Communications

  Yuan Zhou, Rose Qingyang Hu, Yi Qian

• Generative Subspace Adversarial Active Learning for Outlier Detection in Multiple Views of High-dimensional Data

  Jose Cribeiro-Ramallo, Vadim Arzamasov, Federico Matteucci, Denis Wambold, Klemens Böhm

2024-04-19

• How Real Is Real? A Human Evaluation Framework for Unrestricted Adversarial Examples

  Dren Fazlija, Arkadij Orlov, Johanna Schrader, Monty-Maximilian Zühlke, Michael Rohs, Daniel Kudenko

• A Clean-graph Backdoor Attack against Graph Convolutional Networks with Poisoned Label Only

  Jiazhu Dai, Haoyu Sun

• AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation

  Heqi Peng, Yunhong Wang, Ruijie Yang, Beichen Li, Rui Wang, Yuanfang Guo

• MLSD-GAN -- Generating Strong High Quality Face Morphing Attacks using Latent Semantic Disentanglement

  Aravinda Reddy PN, Raghavendra Ramachandra, Krothapalli Sreenivasa Rao, Pabitra Mitra

• PATE-TripleGAN: Privacy-Preserving Image Synthesis with Gaussian Differential Privacy

  Zepeng Jiang, Weiwei Ni, Yifan Zhang

• Robust CLIP-Based Detector for Exposing Diffusion Model-Generated Images

  Santosh, Li Lin, Irene Amerini, Xin Wang, Shu Hu

• SA-Attack: Speed-adaptive stealthy adversarial attack on trajectory prediction

  Huilin Yin, Jiaxiang Li, Pengju Zhen, Jun Yan

• LSP Framework: A Compensatory Model for Defeating Trigger Reverse Engineering via Label Smoothing Poisoning

  Beichen Li, Yuanfang Guo, Heqi Peng, Yangxi Li, Yunhong Wang

• Defending against Data Poisoning Attacks in Federated Learning via User Elimination

  Nick Galanis

• The Power of Words: Generating PowerShell Attacks from Natural Language

  Pietro Liguori, Christian Marescalco, Roberto Natella, Vittorio Orbinato, Luciano Pianese

• Physical Backdoor Attack can Jeopardize Driving with Vision-Large-Language Models

  Zhenyang Ni, Rui Ye, Yuxi Wei, Zhen Xiang, Yanfeng Wang, Siheng Chen

• Privacy-Preserving Debiasing using Data Augmentation and Machine Unlearning

  Zhixin Pan, Emma Andrews, Laura Chang, Prabhat Mishra

• DeepFake-O-Meter v2.0: An Open Platform for DeepFake Detection

  Shuwei Hou, Yan Ju, Chengzhe Sun, Shan Jia, Lipeng Ke, Riky Zhou, Anita Nikolich, Siwei Lyu

• CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models

  Manish Bhatt, Sahana Chennabasappa, Yue Li, Cyrus Nikolaidis, Daniel Song, Shengye Wan, Faizan Ahmad, Cornelius Aschermann, Yaohui Chen, Dhaval Kapil, David Molnar, Spencer Whitman, Joshua Saxe

2024-04-18

• Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors

  Raz Lapid, Almog Dubin, Moshe Sipper

• Proteus: Preserving Model Confidentiality during Graph Optimizations

  Yubo Gao, Maryam Haghifam, Christina Giannoula, Renbo Tu, Gennady Pekhimenko, Nandita Vijaykumar

• Introducing v0.5 of the AI Safety Benchmark from MLCommons

  Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Sujata Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd, Felix Juefei-Xu, Foutse Khomh, Bhavya Kailkhura, Hannah Rose Kirk, Kevin Klyman, Chris Knotz, Michael Kuchnik, Shachi H. Kumar, Chris Lengerich, Bo Li, Zeyi Liao, Eileen Peters Long, Victor Lu, Yifan Mai, et al. (46 additional authors not shown)

• Advancing the Robustness of Large Language Models through Self-Denoised Smoothing

  Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang, Wenqi Fan, Qing Li, Yang Zhang, Gaowen Liu, Sijia Liu, Shiyu Chang

• Enhance Robustness of Language Models Against Variation Attack through Graph Integration

  Zi Xiong, Lizhi Qing, Yangyang Kang, Jiawei Liu, Hongsong Li, Changlong Sun, Xiaozhong Liu, Wei Lu

• Uncovering Safety Risks in Open-source LLMs through Concept Activation Vector

  Zhihao Xu, Ruixuan Huang, Xiting Wang, Fangzhao Wu, Jing Yao, Xing Xie

• Utilizing Adversarial Examples for Bias Mitigation and Accuracy Enhancement

  Pushkar Shukla, Dhruv Srikanth, Lee Cohen, Matthew Turk

• FedMID: A Data-Free Method for Using Intermediate Outputs as a Defense Mechanism Against Poisoning Attacks in Federated Learning

  Sungwon Han, Hyeonho Song, Sungwon Park, Meeyoung Cha

• A Mean-Field Analysis of Neural Gradient Descent-Ascent: Applications to Functional Conditional Moment Equations

  Yuchen Zhu, Yufeng Zhang, Zhaoran Wang, Zhuoran Yang, Xiaohong Chen

• KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning

  Marco Arazzi, Serena Nicolazzo, Antonino Nocera

2024-04-17

• TransLinkGuard: Safeguarding Transformer Models Against Model Stealing in Edge Deployment

  Qinfeng Li, Zhiqiang Shen, Zhenghan Qin, Yangfan Xie, Xuhong Zhang, Tianyu Du, Jianwei Yin

• Sampling-based Pseudo-Likelihood for Membership Inference Attacks

  Masahiro Kaneko, Youmi Ma, Yuki Wata, Naoaki Okazaki

• A Federated Learning Approach to Privacy Preserving Offensive Language Identification

  Marcos Zampieri, Damith Premasiri, Tharindu Ranasinghe

• GenFighter: A Generative and Evolutive Textual Attack Removal

  Md Athikul Islam, Edoardo Serra, Sushil Jajodia

• The Victim and The Beneficiary: Exploiting a Poisoned Model to Train a Clean Model on Poisoned Data

  Zixuan Zhu, Rui Wang, Cong Zou, Lihua Jing

• Detector Collapse: Backdooring Object Detection to Catastrophic Overload or Blindness

  Hangtao Zhang, Shengshan Hu, Yichen Wang, Leo Yu Zhang, Ziqi Zhou, Xianlong Wang, Yanjun Zhang, Chao Chen

• Clipped SGD Algorithms for Privacy Preserving Performative Prediction: Bias Amplification and Remedies

  Qiang Li, Michal Yemini, Hoi-To Wai

• Exploring DNN Robustness Against Adversarial Attacks Using Approximate Multipliers

  Mohammad Javad Askarizadeh, Ebrahim Farahmand, Jorge Castro-Godinez, Ali Mahani, Laura Cabrera-Quiros, Carlos Salazar-Garcia

• A Secure and Trustworthy Network Architecture for Federated Learning Healthcare Applications

  Antonio Boiano, Marco Di Gennaro, Luca Barbieri, Michele Carminati, Monica Nicoli, Alessandro Redondi, Stefano Savazzi, Albert Sund Aillet, Diogo Reis Santos, Luigi Serio

2024-04-16

• Private Attribute Inference from Images with Vision-Language Models

  Batuhan Tömekçe, Mark Vero, Robin Staab, Martin Vechev

• Towards a Novel Perspective on Adversarial Examples Driven by Frequency

  Zhun Zhang, Yi Zeng, Qihe Liu, Shijie Zhou

• Unveiling the Misuse Potential of Base Large Language Models via In-Context Learning

  Xiao Wang, Tianze Chen, Xianjun Yang, Qi Zhang, Xun Zhao, Dahua Lin

• Self-playing Adversarial Language Game Enhances LLM Reasoning

  Pengyu Cheng, Tianhao Hu, Han Xu, Zhisong Zhang, Yong Dai, Lei Han, Nan Du

• Efficiently Adversarial Examples Generation for Visual-Language Models under Targeted Transfer Scenarios using Diffusion Models

  Qi Guo, Shanmin Pang, Xiaojun Jia, Qing Guo

• Adversarial Identity Injection for Semantic Face Image Synthesis

  Giuseppe Tarollo, Tomaso Fontanini, Claudio Ferrari, Guido Borghi, Andrea Prati

• Do Counterfactual Examples Complicate Adversarial Training?

  Eric Yeats, Cameron Darwin, Eduardo Ortega, Frank Liu, Hai Li

• Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback

  Qiwei Di, Jiafan He, Quanquan Gu

• Differentially Private Optimization with Sparse Gradients

  Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

2024-04-15

• Privacy at a Price: Exploring its Dual Impact on AI Fairness

  Mengmeng Yang, Ming Ding, Youyang Qu, Wei Ni, David Smith, Thierry Rakotoarivelo

• Watermark-embedded Adversarial Examples for Copyright Protection against Diffusion Models

  Peifei Zhu, Tsubasa Takahashi, Hirokatsu Kataoka

• Improving Weakly-Supervised Object Localization Using Adversarial Erasing and Pseudo Label

  Byeongkeun Kang, Sinhae Cha, Yeejin Lee

• Beyond Noise: Privacy-Preserving Decentralized Learning with Virtual Nodes

  Sayan Biswas, Mathieu Even, Anne-Marie Kermarrec, Laurent Massoulie, Rafael Pires, Rishi Sharma, Martijn de Vos

• Privacy-Preserving Intrusion Detection using Convolutional Neural Networks

  Martin Kodys, Zhongmin Dai, Vrizlynn L. L. Thing

• Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing

  Song Xia, Yu Yi, Xudong Jiang, Henghui Ding

• Ti-Patch: Tiled Physical Adversarial Patch for no-reference video quality metrics

  Victoria Leonenkova, Ekaterina Shumitskaya, Anastasia Antsiferova, Dmitriy Vatolin

• On the Efficiency of Privacy Attacks in Federated Learning

  Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, Yanzhao Wu

• Privacy-Preserving Federated Unlearning with Certified Client Removal

  Ziyao Liu, Huanyi Ye, Yu Jiang, Jiyuan Shen, Jiale Guo, Ivan Tjuawinata, Kwok-Yan Lam

• Deceiving to Enlighten: Coaxing LLMs to Self-Reflection for Enhanced Bias Detection and Mitigation

  Ruoxi Cheng, Haoxuan Ma, Shuirong Cao

• AIGeN: An Adversarial Approach for Instruction Generation in VLN

  Niyati Rawal, Roberto Bigazzi, Lorenzo Baraldi, Rita Cucchiara

• Black-box Adversarial Transferability: An Empirical Study in Cybersecurity Perspective

  Khushnaseeb Roshan, Aasim Zafar

2024-04-14

• Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning

  Tanveer Khan, Mindaugas Budzys, Antonis Michalas

• FaceCat: Enhancing Face Recognition Security with a Unified Generative Model Framework

  Jiawei Chen, Xiao Yang, Yinpeng Dong, Hang Su, Jianteng Peng, Zhaoxia Yin

• Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies

  Brian R. Bartoldson, James Diffenderfer, Konstantinos Parasyris, Bhavya Kailkhura

2024-04-13

• Proof-of-Learning with Incentive Security

  Zishuo Zhao, Zhixuan Fang, Xuechao Wang, Yuan Zhou

• CodeCloak: A Method for Evaluating and Mitigating Code Leakage by LLM Code Assistants

  Amit Finkman, Eden Bar-Kochva, Avishag Shapira, Dudu Mimran, Yuval Elovici, Asaf Shabtai

• Stability and Generalization in Free Adversarial Training

  Xiwei Cheng, Kexin Fu, Farzan Farnia

• Multimodal Attack Detection for Action Recognition Models

  Furkan Mumcu, Yasin Yilmaz

2024-04-12

• A Survey of Neural Network Robustness Assessment in Image Recognition

  Jie Wang, Jun Ai, Minyan Lu, Haoran Su, Dan Yu, Yutao Zhang, Junda Zhu, Jingyu Liu

• Adversarial Imitation Learning via Boosting

  Jonathan D. Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun

• VertAttack: Taking advantage of Text Classifiers' horizontal vision

  Jonathan Rusert

• Practical Region-level Attack against Segment Anything Models

  Yifan Shen, Zhengyuan Li, Gang Wang

• Struggle with Adversarial Defense? Try Diffusion

  Yujie Li, Yanbin Wang, Haitao xu, Bin Liu, Jianguo Sun, Zhenhao Guo, Wenrui Ma

• Counterfactual Explanations for Face Forgery Detection via Adversarial Removal of Artifacts

  Yang Li, Songlin Yang, Wei Wang, Ziwen He, Bo Peng, Jing Dong

• Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues

  Xianhua He, Dashuang Liang, Song Yang, Zhanlong Hao, Hui Ma, Binjie Mao, Xi Li, Yao Wang, Pengfei Yan, Ajian Liu

• On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth Estimation

  Agneet Chatterjee, Tejas Gokhale, Chitta Baral, Yezhou Yang

• Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing

  Cui Zhang, Xiao Xu, Qiong Wu, Pingyi Fan, Qiang Fan, Huiling Zhu, Jiangzhou Wang

• FCert: Certifiably Robust Few-Shot Classification in the Era of Foundation Models

  Yanting Wang, Wei Zou, Jinyuan Jia

• LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models

  Juntaek Lim, Youngeun Kwon, Ranggi Hwang, Kiwan Maeng, G. Edward Suh, Minsoo Rhu

• PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis

  Dipkamal Bhusal, Md Tanvirul Alam, Monish K. Veerabhadran, Michael Clifford, Sara Rampazzi, Nidhi Rastogi

2024-04-11

• Differentially Private GANs for Generating Synthetic Indoor Location Data

  Vahideh Moghtadaiee, Mina Alishahi, Milad Rabiei

• Differentially Private Reinforcement Learning with Self-Play

  Dan Qiao, Yu-Xiang Wang

• Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing

  ZhenZhe Gao, Zhenjun Tang, Zhaoxia Yin, Baoyuan Wu, Yue Lu

• AmpleGCG: Learning a Universal and Transferable Generative Model of Adversarial Suffixes for Jailbreaking Both Open and Closed LLMs

  Zeyi Liao, Huan Sun

• Privacy preserving layer partitioning for Deep Neural Network models

  Kishore Rajasekar, Randolph Loh, Kar Wai Fok, Vrizlynn L. L. Thing

• Enhancing Network Intrusion Detection Performance using Generative Adversarial Networks

  Xinxing Zhao, Kar Wai Fok, Vrizlynn L. L. Thing

• Backdoor Contrastive Learning via Bi-level Trigger Optimization

  Weiyu Sun, Xinyu Zhang, Hao Lu, Yingcong Chen, Ting Wang, Jinghui Chen, Lu Lin

• Latent Guard: a Safety Framework for Text-to-image Generation

  Runtao Liu, Ashkan Khakzar, Jindong Gu, Qifeng Chen, Philip Torr, Fabio Pizzati

• LLM Agents can Autonomously Exploit One-day Vulnerabilities

  Richard Fang, Rohan Bindu, Akul Gupta, Daniel Kang

• Persistent Classification: A New Approach to Stability of Data and Adversarial Examples

  Brian Bell, Michael Geyer, David Glickenstein, Keaton Hamm, Carlos Scheidegger, Amanda Fernandez, Juston Moore

• Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization

  Runqi Lin, Chaojian Yu, Tongliang Liu

• CodeFort: Robust Training for Code Generation Models

  Yuhao Zhang, Shiqi Wang, Haifeng Qian, Zijian Wang, Mingyue Shang, Linbo Liu, Sanjay Krishna Gouda, Baishakhi Ray, Murali Krishna Ramanathan, Xiaofei Ma, Anoop Deoras

2024-04-10

• Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks

  Kavita Kumari, Murtuza Jadliwala, Sumit Kumar Jha, Anindya Maiti

• SafeGen: Mitigating Unsafe Content Generation in Text-to-Image Models

  Xinfeng Li, Yuchen Yang, Jiangyi Deng, Chen Yan, Yanjiao Chen, Xiaoyu Ji, Wenyuan Xu

• How to Craft Backdoors with Unlabeled Data Alone?

  Yifei Wang, Wenhan Ma, Yisen Wang

• Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data

  Yu Qiao, Chaoning Zhang, Apurba Adhikary, Choong Seon Hong

• Adversarial purification for no-reference image-quality metrics: applicability study and new methods

  Aleksandr Gushchin, Anna Chistyakova, Vladislav Minashkin, Anastasia Antsiferova, Dmitriy Vatolin

• Simpler becomes Harder: Do LLMs Exhibit a Coherent Behavior on Simplified Corpora?

  Miriam Anschütz, Edoardo Mosca, Georg Groh

• Poisoning Prevention in Federated Learning and Differential Privacy via Stateful Proofs of Execution

  Norrathep Rattanavipanon, Ivan de Oliviera Nunes

2024-04-09

• Differential Privacy for Anomaly Detection: Analyzing the Trade-off Between Privacy and Explainability

  Fatima Ezzeddine, Mirna Saad, Omran Ayoub, Davide Andreoletti, Martin Gjoreski, Ihab Sbeity, Marc Langheinrich, Silvia Giordano

• LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks

  Jianlang Chen, Xuhong Ren, Qing Guo, Felix Juefei-Xu, Di Lin, Wei Feng, Lei Ma, Jianjun Zhao

• On adversarial training and the 1 Nearest Neighbor classifier

  Amir Hagai, Yair Weiss

• Towards Robust Domain Generation Algorithm Classification

  Arthur Drichel, Marc Meyer, Ulrike Meyer

• Privacy-preserving Scanpath Comparison for Pervasive Eye Tracking

  Suleyman Ozdel, Efe Bozkir, Enkelejda Kasneci

• Sandwich attack: Multi-language Mixture Adaptive Attack on LLMs

  Bibek Upadhayay, Vahid Behzadan

• Towards Building a Robust Toxicity Predictor

  Dmitriy Bespalov, Sourav Bhabesh, Yi Xiang, Liutong Zhou, Yanjun Qi

2024-04-08

• SoK: Gradient Leakage in Federated Learning

  Jiacheng Du, Jiahui Hu, Zhibo Wang, Peng Sun, Neil Zhenqiang Gong, Kui Ren

• Best-of-Venom: Attacking RLHF by Injecting Poisoned Preference Data

  Tim Baumgärtner, Yang Gao, Dana Alon, Donald Metzler

• Investigating the Impact of Quantization on Adversarial Robustness

  Qun Li, Yuan Meng, Chen Tang, Jiacheng Jiang, Zhi Wang

• David and Goliath: An Empirical Evaluation of Attacks and Defenses for QNNs at the Deep Edge

  Miguel Costa, Sandro Pinto

• Semantic Stealth: Adversarial Text Attacks on NLP Using Several Methods

  Roopkatha Dey, Aivy Debnath, Sayak Kumar Dutta, Kaustav Ghosh, Arijit Mitra, Arghya Roy Chowdhury, Jaydip Sen

• Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey

  Naveen Karunanayake, Ravin Gunawardena, Suranga Seneviratne, Sanjay Chawla

• BruSLeAttack: A Query-Efficient Score-Based Black-Box Sparse Adversarial Attack

  Viet Quoc Vo, Ehsan Abbasnejad, Damith C. Ranasinghe

• Certified PEFTSmoothing: Parameter-Efficient Fine-Tuning with Randomized Smoothing

  Chengyan Fu, Wenjie Wang

• Flexible Fairness Learning via Inverse Conditional Permutation

  Yuheng Lai, Leying Guan

• Enabling Privacy-Preserving Cyber Threat Detection with Federated Learning

  Yu Bi, Yekai Li, Xuan Feng, Xianghang Mi

• Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning

  Ruiqi Zhang, Licong Lin, Yu Bai, Song Mei

• Eraser: Jailbreaking Defense in Large Language Models via Unlearning Harmful Knowledge

  Weikai Lu, Ziqian Zeng, Jianwei Wang, Zhengdong Lu, Zelin Chen, Huiping Zhuang, Cen Chen

• Privacy-Preserving Deep Learning Using Deformable Operators for Secure Task Learning

  Fabian Perez, Jhon Lopez, Henry Arguello

• Quantum Adversarial Learning for Kernel Methods

  Giuseppe Montalbano, Leonardo Banchi

2024-04-07

• Inference-Time Rule Eraser: Distilling and Removing Bias Rules to Mitigate Bias in Deployed Models

  Yi Zhang, Jitao Sang

• Hidden You Malicious Goal Into Benigh Narratives: Jailbreak Large Language Models through Logic Chain Injection

  Zhilong Wang, Yebo Cao, Peng Liu

• SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials

  Mael Jullien, Marco Valentino, André Freitas

• How much reliable is ChatGPT's prediction on Information Extraction under Input Perturbations?

  Ishani Mondal, Abhilasha Sancheti

• Privacy-Preserving Traceable Functional Encryption for Inner Product

  Muyao Qiu, Jinguang Han

2024-04-06

• Trustless Audits without Revealing Data or Models

  Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang

• Data Poisoning Attacks on Off-Policy Policy Evaluation Methods

  Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju

• D$^3$: Scaling Up Deepfake Detection by Learning from Discrepancy

  Yongqi Yang, Zhihao Qian, Ye Zhu, Yu Wu

• Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training

  Shizhan Gong, Qi Dou, Farzan Farnia

• CANEDERLI: On The Impact of Adversarial Training and Transferability on CAN Intrusion Detection Systems

  Francesco Marchiori, Mauro Conti

• Goal-guided Generative Prompt Injection Attack on Large Language Models

  Chong Zhang, Mingyu Jin, Qinkai Yu, Chengzhi Liu, Haochen Xue, Xiaobo Jin

• ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming

  Simone Tedeschi, Felix Friedrich, Patrick Schramowski, Kristian Kersting, Roberto Navigli, Huu Nguyen, Bo Li

2024-04-05

• Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning

  K Naveen Kumar, C Krishna Mohan, Aravind Machiry

• Watermark-based Detection and Attribution of AI-Generated Content

  Zhengyuan Jiang, Moyang Guo, Yuepeng Hu, Neil Zhenqiang Gong

• Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism

  Trilokesh Ranjan Sarkar, Nilanjan Das, Pralay Sankar Maitra, Bijoy Some, Ritwik Saha, Orijita Adhikary, Bishal Bose, Jaydip Sen

• Re-pseudonymization Strategies for Smart Meter Data Are Not Robust to Deep Learning Profiling Attacks

  Ana-Maria Cretu, Miruna Rusu, Yves-Alexandre de Montjoye

• You Can Use But Cannot Recognize: Preserving Visual Privacy in Deep Neural Networks

  Qiushi Li, Yan Zhang, Ju Ren, Qi Li, Yaoxue Zhang

• Increased LLM Vulnerabilities from Fine-tuning and Quantization

  Divyanshu Kumar, Anurakt Kumar, Sahil Agarwal, Prashanth Harshangi

2024-04-04

• Knowledge Distillation-Based Model Extraction Attack using Private Counterfactual Explanations

  Fatima Ezzeddine, Omran Ayoub, Silvia Giordano

• Learn When (not) to Trust Language Models: A Privacy-Centric Adaptive Model-Aware Approach

  Chengkai Huang, Rui Wang, Kaige Xie, Tong Yu, Lina Yao

• A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking The Privacy-Utility Trade-off

  Stephen Meisenbacher, Nihildev Nandakumar, Alexandra Klymenko, Florian Matthes

• Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks?

  Shuo Chen, Zhen Han, Bailan He, Zifeng Ding, Wenqian Yu, Philip Torr, Volker Tresp, Jindong Gu

• Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks

  Lei Zhang, Yuhang Zhou, Yi Yang, Xinbo Gao

• Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning

  Hongsheng Hu, Shuo Wang, Tian Dong, Minhui Xue

• Privacy-Enhancing Technologies for Artificial Intelligence-Enabled Systems

  Liv d'Aliberti, Evan Gronberg, Joseph Kovba

• Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators for Fast Private Inference in Homomorphic Encryption

  Jianming Tong, Jingtian Dang, Anupam Golder, Callie Hao, Arijit Raychowdhury, Tushar Krishna

2024-04-03

• JailBreakV-28K: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks

  Weidi Luo, Siyuan Ma, Xiaogeng Liu, Xiaoyu Guo, Chaowei Xiao

• Adversarial Attacks and Dimensionality in Text Classifiers

  Nandish Chattopadhyay, Atreya Goswami, Anupam Chattopadhyay

• Learn to Disguise: Avoid Refusal Responses in LLM's Defense via a Multi-agent Attacker-Disguiser Game

  Qianqiao Xu, Zhiliang Tian, Hongyan Wu, Zhen Huang, Yiping Song, Feng Liu, Dongsheng Li

2024-04-02

• Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models

  Jiachen Ma, Anda Cao, Zhiqing Xiao, Jie Zhang, Chao Ye, Junbo Zhao

• Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

  Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion

• Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack

  Ying Zhou, Ben He, Le Sun

• Red-Teaming Segment Anything Model

  Krzysztof Jankowski, Bartlomiej Sobieski, Mateusz Kwiatkowski, Jakub Szulc, Michal Janik, Hubert Baniecki, Przemyslaw Biecek

• Towards Robust 3D Pose Transfer with Adversarial Learning

  Haoyu Chen, Hao Tang, Ehsan Adeli, Guoying Zhao

• Exploring Backdoor Vulnerabilities of Chat Models

  Yunzhuo Hao, Wenkai Yang, Yankai Lin

2024-04-01

• BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks

  Zhiyuan Cheng, Zhaoyi Liu, Tengda Guo, Shiwei Feng, Dongfang Liu, Mingjie Tang, Xiangyu Zhang

• Multi-granular Adversarial Attacks against Black-box Neural Ranking Models

  Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan, Xueqi Cheng

• UFID: A Unified Framework for Input-level Backdoor Detection on Diffusion Models

  Zihan Guan, Mengxuan Hu, Sheng Li, Anil Vullikanti

2024-03-31

• An Unsupervised Adversarial Autoencoder for Cyber Attack Detection in Power Distribution Grids

  Mehdi Jabbari Zideh, Mohammad Reza Khalghani, Sarika Khushalani Solanki

2024-03-30

• STBA: Towards Evaluating the Robustness of DNNs for Query-Limited Black-box Scenario

  Renyang Liu, Kwok-Yan Lam, Wei Zhou, Sixing Wu, Jun Zhao, Dongting Hu, Mingming Gong

2024-03-29

• Benchmarking the Robustness of Temporal Action Detection Models Against Temporal Corruptions

  Runhao Zeng, Xiaoyong Chen, Jiaming Liang, Huisi Wu, Guangzhong Cao, Yong Guo

2024-03-28

• MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models

  Yanting Wang, Hongye Fu, Wei Zou, Jinyuan Jia

• MedBN: Robust Test-Time Adaptation against Malicious Test Samples

  Hyejin Park, Jeongyeon Hwang, Sunung Mun, Sangdon Park, Jungseul Ok

• Towards Understanding Dual BN In Hybrid Adversarial Training

  Chenshuang Zhang, Chaoning Zhang, Kang Zhang, Axi Niu, Junmo Kim, In So Kweon

• Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset

  Janis Goldzycher, Paul Röttger, Gerold Schneider

2024-03-27

• Manipulating Neural Path Planners via Slight Perturbations

  Zikang Xiong, Suresh Jagannathan

• CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection

  Jiayi Zhu, Qing Guo, Felix Juefei-Xu, Yihao Huang, Yang Liu, Geguang Pu

• Safe and Robust Reinforcement-Learning: Principles and Practice

  Taku Yamagata, Raul Santos-Rodriguez

• Bayesian Learned Models Can Detect Adversarial Malware For Free

  Bao Gia Doan, Dang Quang Nguyen, Paul Montague, Tamas Abraham, Olivier De Vel, Seyit Camtepe, Salil S. Kanhere, Ehsan Abbasnejad, Damith C. Ranasinghe

• MisGUIDE : Defense Against Data-Free Deep Learning Model Extraction

  Mahendra Gurve, Sankar Behera, Satyadev Ahlawat, Yamuna Prasad

• Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning

  Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi, Vineet Gundecha, Avisek Naug, Sahand Ghorbanpour

2024-03-26

• Out-of-distribution Rumor Detection via Test-Time Adaptation

  Xiang Tao, Mingqing Zhang, Qiang Liu, Shu Wu, Liang Wang

• DataCook: Crafting Anti-Adversarial Examples for Healthcare Data Copyright Protection

  Sihan Shang, Jiancheng Yang, Zhenglong Sun, Pascal Fua

• UADA3D: Unsupervised Adversarial Domain Adaptation for 3D Object Detection with Sparse LiDAR and Large Domain Gaps

  Maciej K Wozniak, Mattias Hansson, Marko Thiel, Patric Jensfelt

• Optimization-based Prompt Injection Attack to LLM-as-a-Judge

  Jiawen Shi, Zenghui Yuan, Yinuo Liu, Yue Huang, Pan Zhou, Lichao Sun, Neil Zhenqiang Gong

• Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving

  Junhao Zheng, Chenhao Lin, Jiahao Sun, Zhengyu Zhao, Qian Li, Chao Shen

• Boosting Adversarial Training via Fisher-Rao Norm-based Regularization

  Xiangyu Yin, Wenjie Ruan

• Securing GNNs: Explanation-Based Identification of Backdoored Training Graphs

  Jane Downer, Ren Wang, Binghui Wang

• Targeted Visualization of the Backbone of Encoder LLMs

  Isaac Roberts, Alexander Schulz, Luca Hermes, Barbara Hammer

2024-03-25

• $\textit{LinkPrompt}$: Natural and Universal Adversarial Attacks on Prompt-based Language Models

  Yue Xu, Wenjie Wang

• The Anatomy of Adversarial Attacks: Concept-based XAI Dissection

  Georgii Mikriukov, Gesina Schwalbe, Franz Motzkus, Korinna Bade

• Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion

  Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam Fowl, Aniruddha Saha, Jonas Geiping, Andrew Gordon Wilson, Rama Chellappa, Tom Goldstein, Micah Goldblum

• Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models

  Kaikang Zhao, Xi Chen, Wei Huang, Liuxin Ding, Xianglong Kong, Fan Zhang

• Revealing Vulnerabilities of Neural Networks in Parameter Learning and Defense Against Explanation-Aware Backdoors

  Md Abdul Kadir, GowthamKrishna Addluri, Daniel Sonntag

• CipherFormer: Efficient Transformer Private Inference with Low Round Complexity

  Weize Wang, Yi Kuang

• Task-Agnostic Detector for Insertion-Based Backdoor Attacks

  Weimin Lyu, Xiao Lin, Songzhu Zheng, Lu Pang, Haibin Ling, Susmit Jha, Chao Chen

• LOTUS: Evasive and Resilient Backdoor Attacks through Sub-Partitioning

  Siyuan Cheng, Guanhong Tao, Yingqi Liu, Guangyu Shen, Shengwei An, Shiwei Feng, Xiangzhe Xu, Kaiyuan Zhang, Shiqing Ma, Xiangyu Zhang

2024-03-24

• Unlearning Backdoor Threats: Enhancing Backdoor Defense in Multimodal Contrastive Learning via Local Token Unlearning

  Siyuan Liang, Kuanrong Liu, Jiajun Gong, Jiawei Liang, Yuan Xun, Ee-Chien Chang, Xiaochun Cao

• Robust Diffusion Models for Adversarial Purification

  Guang Lin, Zerui Tao, Jianhai Zhang, Toshihisa Tanaka, Qibin Zhao

• Subspace Defense: Discarding Adversarial Perturbations by Learning a Subspace for Clean Signals

  Rui Zheng, Yuhao Zhou, Zhiheng Xi, Tao Gui, Qi Zhang, Xuanjing Huang

2024-03-23

• Adversarial Defense Teacher for Cross-Domain Object Detection under Poor Visibility Conditions

  Kaiwen Wang, Yinzhe Shen, Martin Lauer

• An Embarrassingly Simple Defense Against Backdoor Attacks On SSL

  Aryan Satpathy, Nilaksh, Dhruva Rajwade

2024-03-22

• A Transfer Attack to Image Watermarks

  Yuepeng Hu, Zhengyuan Jiang, Moyang Guo, Neil Gong

• Clean-image Backdoor Attacks

  Dazhong Rong, Shuheng Shen, Xinyi Fu, Peng Qian, Jianhai Chen, Qinming He, Xing Fu, Weiqiang Wang

• Robust optimization for adversarial learning with finite sample complexity guarantees

  André Bertolace, Konstatinos Gatsis, Kostas Margellos

• Twin Auto-Encoder Model for Learning Separable Representation in Cyberattack Detection

  Phai Vu Dinh, Quang Uy Nguyen, Thai Hoang Dinh, Diep N. Nguyen, Bao Son Pham, Eryk Dutkiewicz

• Differentially Private Next-Token Prediction of Large Language Models

  James Flemings, Meisam Razaviyayn, Murali Annavaram

2024-03-21

• SoftPatch: Unsupervised Anomaly Detection with Noisy Data

  Xi Jiang, Ying Chen, Qiang Nie, Yong Liu, Jianlin Liu, Bin-Bin Gao, Jun Liu, Chengjie Wang, Feng Zheng

• Locating and Mitigating Gender Bias in Large Language Models

  Yuchen Cai, Ding Cao, Rongxi Guo, Yaqin Wen, Guiquan Liu, Enhong Chen

• Detoxifying Large Language Models via Knowledge Editing

  Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi, Shumin Deng, Yunzhi Yao, Qishen Zhang, Linyi Yang, Jindong Wang, Huajun Chen

• MMIDR: Teaching Large Language Model to Interpret Multimodal Misinformation via Knowledge Distillation

  Longzheng Wang, Xiaohan Xu, Lei Zhang, Jiarui Lu, Yongxiu Xu, Hongbo Xu, Chuang Zhang

• Adversary-Robust Graph-Based Learning of WSIs

  Saba Heidari Gheshlaghi, Milan Aryal, Nasim Yahyasoltani, Masoud Ganji

• Rethinking Adversarial Inverse Reinforcement Learning: From the Angles of Policy Imitation and Transferable Reward Recovery

  Yangchun Zhang, Yirui Zhou

• Improving the Robustness of Large Language Models via Consistency Alignment

  Zhao Yukun, Yan Lingyong, Sun Weiwei, Xing Guoliang, Wang Shuaiqiang, Meng Chong, Cheng Zhicong, Ren Zhaochun, Yin Dawei

• Rethinking Adversarial Inverse Reinforcement Learning: From the Angles of Policy Imitation and Transferable Reward Recovery

  Yangchun Zhang, Yirui Zhou

• Adversary-Augmented Simulation to evaluate client-fairness on HyperLedger Fabric

  Erwan Mahe, Rouwaida Abdallah, Sara Tucci-Piergiovanni, Pierre-Yves Piriou

• FIT-RAG: Black-Box RAG with Factual Information and Token Reduction

  Yuren Mao, Xuemei Dong, Wenyi Xu, Yunjun Gao, Bin Wei, Ying Zhang

• Adversary-Robust Graph-Based Learning of WSIs

  Saba Heidari Gheshlaghi, Milan Aryal, Nasim Yahyasoltani, Masoud Ganji

• Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations

  Xun Lin, Yi Yu, Song Xia, Jue Jiang, Haoran Wang, Zitong Yu, Yizhong Liu, Ying Fu, Shuai Wang, Wenzhong Tang, Alex Kot

• HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption

  Seewoo Lee, Garam Lee, Jung Woo Kim, Junbum Shin, Mun-Kyu Lee

• Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures

  Sayanton V. Dibbo, Adam Breuer, Juston Moore, Michael Teti

• Protected group bias and stereotypes in Large Language Models

  Hadas Kotek, David Q. Sun, Zidi Xiu, Margit Bowler, Christopher Klein

• Diffusion Attack: Leveraging Stable Diffusion for Naturalistic Image Attacking

  Qianyu Guo, Jiaming Fu, Yawen Lu, Dongming Gan

2024-03-20

• BadEdit: Backdooring large language models by model editing

  Yanzhou Li, Tianlin Li, Kangjie Chen, Jian Zhang, Shangqing Liu, Wenhan Wang, Tianwei Zhang, Yang Liu

• Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection

  Davide Alessandro Coccomini, Roberto Caldelli, Claudio Gennaro, Giuseppe Fiameni, Giuseppe Amato, Fabrizio Falchi

• Have You Poisoned My Data? Defending Neural Networks against Data Poisoning

  Fabio De Gaspari, Dorjan Hitaj, Luigi V. Mancini

• Adversarial Attacks and Defenses in Automated Control Systems: A Comprehensive Benchmark

  Vitaliy Pozdnyakov, Aleksandr Kovalenko, Ilya Makarov, Mikhail Drobyshevskiy, Kirill Lukyanov

• Reducing Large Language Model Bias with Emphasis on 'Restricted Industries': Automated Dataset Augmentation and Prejudice Quantification

  Devam Mondal, Carlo Lipizzi

• Multi-Modal Hallucination Control by Visual Information Grounding

  Alessandro Favero, Luca Zancato, Matthew Trager, Siddharth Choudhary, Pramuditha Perera, Alessandro Achille, Ashwin Swaminathan, Stefano Soatto

• Optimal Transport for Fairness: Archival Data Repair using Small Research Data Sets

  Abigail Langbridge, Anthony Quinn, Robert Shorten

2024-03-19

• Electioneering the Network: Dynamic Multi-Step Adversarial Attacks for Community Canvassing

  Saurabh Sharma, Ambuj SIngh

• FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization

  Cheng Yang, Jixi Liu, Yunhe Yan, Chuan Shi

• RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content

  Zhuowen Yuan, Zidi Xiong, Yi Zeng, Ning Yu, Ruoxi Jia, Dawn Song, Bo Li

• Robust NAS under adversarial training: benchmark, theory, and beyond

  Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios G Chrysos, Volkan Cevher

• ADAPT to Robustify Prompt Tuning Vision Transformers

  Masih Eskandar, Tooba Imtiaz, Zifeng Wang, Jennifer Dy

• Analyzing the Impact of Partial Sharing on the Resilience of Online Federated Learning Against Model Poisoning Attacks

  Ehsan Lari, Vinay Chakravarthi Gogineni, Reza Arablouei, Stefan Werner

2024-03-18

• Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural Networks

  Andrea Venturi, Dario Stabili, Mirco Marchetti

• A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models

  Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres, Darlene Neal, Mercy Asiedu, Awa Dieng, Nenad Tomasev, Qazi Mamunur Rashid, Shekoofeh Azizi, Negar Rostamzadeh, Liam G. McCoy, Leo Anthony Celi, Yun Liu, Mike Schaekermann, Alanna Walton, Alicia Parrish, Chirag Nagpal, Preeti Singh, Akeiylah Dewitt, Philip Mansfield, Sushant Prakash, Katherine Heller, Alan Karthikesalingam, Christopher Semturs, Joelle Barral, Greg Corrado, Yossi Matias, Jamila Smith-Loud, Ivor Horn, Karan Singhal

• Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization

  Yujia Liu, Chenxi Yang, Dingquan Li, Jianhao Ding, Tingting Jiang

• SSAP: A Shape-Sensitive Adversarial Patch for Comprehensive Disruption of Monocular Depth Estimation in Autonomous Navigation Applications

  Amira Guesmi, Muhammad Abdullah Hanif, Ihsen Alouani, Bassem Ouni, Muhammad Shafique

• LocalStyleFool: Regional Video Style Transfer Attack Using Segment Anything Model

  Yuxin Cao, Jinghao Li, Xi Xiao, Derui Wang, Minhui Xue, Hao Ge, Wei Liu, Guangwu Hu

• Diffusion Denoising as a Certified Defense against Clean-label Poisoning

  Sanghyun Hong, Nicholas Carlini, Alexey Kurakin

• Diffusion-Reinforcement Learning Hierarchical Motion Planning in Adversarial Multi-agent Games

  Zixuan Wu, Sean Ye, Manisha Natarajan, Matthew C. Gombolay

• Improving LoRA in Privacy-preserving Federated Learning

  Youbang Sun, Zitao Li, Yaliang Li, Bolin Ding

• Impart: An Imperceptible and Effective Label-Specific Backdoor Attack

  Jingke Zhao, Zan Wang, Yongwei Wang, Lanjun Wang

• Invisible Backdoor Attack Through Singular Value Decomposition

  Wenmin Chen, Xiaowei Xu

2024-03-17

• RobustSentEmbed: Robust Sentence Embeddings Using Adversarial Self-Supervised Contrastive Learning

  Javad Rafiei Asl, Prajwal Panzade, Eduardo Blanco, Daniel Takabi, Zhipeng Cai

• COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits

  Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li

• A Modified Word Saliency-Based Adversarial Attack on Text Classification Models

  Hetvi Waghela, Sneha Rakshit, Jaydip Sen

2024-03-16

• Improving Adversarial Transferability of Visual-Language Pre-training Models through Collaborative Multimodal Interaction

  Jiyuan Fu, Zhaoyu Chen, Kaixun Jiang, Haijing Guo, Jiafeng Wang, Shuyong Gao, Wenqiang Zhang

• Understanding Robustness of Visual State Space Models for Image Classification

  Chengbin Du, Yanxi Li, Chang Xu

• Adversarial Knapsack and Secondary Effects of Common Information for Cyber Operations

  Jon Goohs, Georgel Savin, Lucas Starks, Josiah Dykstra, William Casey

2024-03-15

• Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries

  Swetha Ganesh, Jiayu Chen, Gugan Thoppe, Vaneet Aggarwal

• Benchmarking Zero-Shot Robustness of Multimodal Foundation Models: A Pilot Study

  Chenguang Wang, Ruoxi Jia, Xin Liu, Dawn Song

• Revisiting Adversarial Training under Long-Tailed Distributions

  Xinli Yue, Ningping Mou, Qian Wang, Lingchen Zhao

• Benchmarking Adversarial Robustness of Image Shadow Removal with Shadow-adaptive Attacks

  Chong Wang, Yi Yu, Lanqing Guo, Bihan Wen

• Mitigating Dialogue Hallucination for Large Multi-modal Models via Adversarial Instruction Tuning

  Dongmin Park, Zhaofang Qian, Guangxing Han, Ser-Nam Lim

• Towards Adversarially Robust Dataset Distillation by Curvature Regularization

  Eric Xue, Yijiang Li, Haoyang Liu, Yifan Shen, Haohan Wang

• Generation is better than Modification: Combating High Class Homophily Variance in Graph Anomaly Detection

  Rui Zhang, Dawei Cheng, Xin Liu, Jie Yang, Yi Ouyang, Xian Wu, Yefeng Zheng

• Federated Learning with Anomaly Detection via Gradient and Reconstruction Analysis

  Zahir Alsulaimawi

• Securing Federated Learning with Control-Flow Attestation: A Novel Framework for Enhanced Integrity and Resilience against Adversarial Attacks

  Zahir Alsulaimawi

• Interactive Trimming against Evasive Online Data Manipulation Attacks: A Game-Theoretic Approach

  Yue Fu, Qingqing Ye, Rong Du, Haibo Hu

• Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency

  Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu

2024-03-14

• ADEdgeDrop: Adversarial Edge Dropping for Robust Graph Neural Networks

  Zhaoliang Chen, Zhihao Wu, Ylli Sadikaj, Claudia Plant, Hong-Ning Dai, Shiping Wang, Wenzhong Guo

• Adversarial Training with OCR Modality Perturbation for Scene-Text Visual Question Answering

  Zhixuan Shen, Haonan Luo, Sijia Li, Tianrui Li

• AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting

  Yu Wang, Xiaogeng Liu, Yu Li, Muhao Chen, Chaowei Xiao

• VDNA-PR: Using General Dataset Representations for Robust Sequential Visual Place Recognition

  Benjamin Ramtoula, Daniele De Martini, Matthew Gadd, Paul Newman

• Impact of Synthetic Images on Morphing Attack Detection Using a Siamese Network

  Juan Tapia, Christoph Busch

• Anomaly Detection by Adapting a pre-trained Vision Language Model

  Yuxuan Cai, Xinwei He, Dingkang Liang, Ao Tong, Xiang Bai

• Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement

  Daiwei Yu, Zhuorong Li, Lina Wei, Canghong Jin, Yun Zhang, Sixian Chan

• Adversarial Fine-tuning of Compressed Neural Networks for Joint Improvement of Robustness and Efficiency

  Hallgrimur Thorsteinsson, Valdemar J Henriksen, Tong Chen, Raghavendra Selvan

• AVIBench: Towards Evaluating the Robustness of Large Vision-Language Model on Adversarial Visual-Instructions

  Hao Zhang, Wenqi Shao, Hong Liu, Yongqiang Ma, Ping Luo, Yu Qiao, Kaipeng Zhang

• Counterfactual contrastive learning: robust representations via causal image synthesis

  Melanie Roschewitz, Fabio De Sousa Ribeiro, Tian Xia, Galvin Khara, Ben Glocker

• Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation

  Yunhao Gou, Kai Chen, Zhili Liu, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung, James T. Kwok, Yu Zhang

• Ciphertext-Only Attack on a Secure $k$-NN Computation on Cloud

  Shyam Murthy, Santosh Kumar Upadhyaya, Srinivas Vivek

• Optimistic Verifiable Training by Controlling Hardware Nondeterminism

  Megha Srivastava, Simran Arora, Dan Boneh

• Evaluating LLMs for Gender Disparities in Notable Persons

  Lauren Rhue, Sofie Goethals, Arun Sundararajan

• Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk

  Zhangheng Li, Junyuan Hong, Bo Li, Zhangyang Wang

• An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models

  Haochen Luo, Jindong Gu, Fengyuan Liu, Philip Torr

• Robust Subgraph Learning by Monitoring Early Training Representations

  Sepideh Neshatfar, Salimeh Yasaei Sekeh

• Counter-Samples: A Stateless Strategy to Neutralize Black Box Adversarial Attacks

  Roey Bokobza, Yisroel Mirsky

2024-03-13

• Robust Decision Aggregation with Adversarial Experts

  Yongkang Guo, Yuqing Kong

• Versatile Defense Against Adversarial Attacks on Image Recognition

  Haibo Zhang, Zhihua Yao, Kouichi Sakurai

• RAF-GI: Towards Robust, Accurate and Fast-Convergent Gradient Inversion Attack in Federated Learning

  Can Liu, Jin Wang, Dongyang Yu

• AIGCs Confuse AI Too: Investigating and Explaining Synthetic Image-induced Hallucinations in Large Vision-Language Models

  Yifei Gao, Jiaqi Wang, Zhiyu Lin, Jitao Sang

• Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks

  Khondoker Murad Hossain, Tim Oates

• SoK: Reducing the Vulnerability of Fine-tuned Language Models to Membership Inference Attacks

  Guy Amit, Abigail Goldsteen, Ariel Farkash

2024-03-12

• Disentangling Policy from Offline Task Representation Learning via Adversarial Data Augmentation

  Chengxing Jia, Fuxiang Zhang, Yi-Chen Li, Chen-Xiao Gao, Xu-Hui Liu, Lei Yuan, Zongzhang Zhang, Yang Yu

• A Bayesian Approach to OOD Robustness in Image Classification

  Prakhar Kaushik, Adam Kortylewski, Alan Yuille

• Exploring Safety Generalization Challenges of Large Language Models via Code

  Qibing Ren, Chang Gao, Jing Shao, Junchi Yan, Xin Tan, Wai Lam, Lizhuang Ma

• Truth-Aware Context Selection: Mitigating the Hallucinations of Large Language Models Being Misled by Untruthful Contexts

  Tian Yu, Shaolei Zhang, Yang Feng

• Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations

  Chenyu You, Yifei Min, Weicheng Dai, Jasjeet S. Sekhon, Lawrence Staib, James S. Duncan

• Backdoor Attack with Mode Mixture Latent Modification

  Hongwei Zhang, Xiaoyin Xu, Dongsheng An, Xianfeng Gu, Min Zhang

• FairRR: Pre-Processing for Group Fairness through Randomized Response

  Xianli Zeng, Joshua Ward, Guang Cheng

• LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

  Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, Ion Stoica

2024-03-11

• Poisoning Programs by Un-Repairing Code: Security Concerns of AI-generated Code

  Cristina Improta

• Data-Independent Operator: A Training-Free Artifact Representation Extractor for Generalizable Deepfake Detection

  Chuangchuang Tan, Ping Liu, RenShuai Tao, Huan Liu, Yao Zhao, Baoyuan Wu, Yunchao Wei

• PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor

  Jaewon Jung, Hongsun Jang, Jaeyong Song, Jinho Lee

• Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification

  Shuai Li, Xiaoguang Ma, Shancheng Jiang, Lu Meng

• Intra-Section Code Cave Injection for Adversarial Evasion Attacks on Windows PE Malware File

  Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam, Moustafa Saleh

• Real is not True: Backdoor Attacks Against Deepfake Detection

  Hong Sun, Ziqiang Li, Lei Liu, Bin Li

• Stealing Part of a Production Language Model

  Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr

• Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning

  Fuseinin Mumuni, Alhassan Mumuni

2024-03-10

• In-context Prompt Learning for Test-time Vision Recognition with Frozen Vision-language Model

  Junhui Yin, Xinyu Zhang, Lin Wu, Xianghua Xie, Xiaojie Wang

• Federated Learning: Attacks, Defenses, Opportunities, and Challenges

  Ghazaleh Shirvani, Saeid Ghasemshirazi, Behzad Beigzadeh

• Attacking Transformers with Feature Diversity Adversarial Perturbation

  Chenxing Gao, Hang Zhou, Junqing Yu, YuTeng Ye, Jiale Cai, Junle Wang, Wei Yang

2024-03-09

• Towards Deviation-Robust Agent Navigation via Perturbation-Aware Contrastive Learning

  Bingqian Lin, Yanxin Long, Yi Zhu, Fengda Zhu, Xiaodan Liang, Qixiang Ye, Liang Lin

• Hard-label based Small Query Black-box Adversarial Attack

  Jeonghwan Park, Paul Miller, Niall McLaughlin

2024-03-08

• Predicting Single-cell Drug Sensitivity by Adaptive Weighted Feature for Adversarial Multi-source Domain Adaptation

  Wei Duan, Hui Liu

• Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume

  Ping Guo, Cheng Gong, Xi Lin, Zhiyuan Yang, Qingfu Zhang

• Overcoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation

  Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu

• Towards Multimodal Sentiment Analysis Debiasing via Bias Purification

  Dingkang Yang, Mingcheng Li, Dongling Xiao, Yang Liu, Kun Yang, Zhaoyu Chen, Yuzheng Wang, Peng Zhai, Ke Li, Lihua Zhang

• The Impact of Quantization on the Robustness of Transformer-based Text Classifiers

  Seyed Parsa Neshaei, Yasaman Boreshban, Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel

• Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds

  Tianrui Lou, Xiaojun Jia, Jindong Gu, Li Liu, Siyuan Liang, Bangyan He, Xiaochun Cao

• Federated Learning Method for Preserving Privacy in Face Recognition System

  Enoch Solomon, Abraham Woubie

• EVD4UAV: An Altitude-Sensitive Benchmark to Evade Vehicle Detection in UAV

  Huiming Sun, Jiacheng Guo, Zibo Meng, Tianyun Zhang, Jianwu Fang, Yuewei Lin, Hongkai Yu

• Adversarial Sparse Teacher: Defense Against Distillation-Based Model Stealing Attacks Using Adversarial Examples

  Eda Yilmaz, Hacer Yalim Keles

2024-03-07

• Privacy-preserving Fine-tuning of Large Language Models through Flatness

  Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei

• A Domain Translation Framework with an Adversarial Denoising Diffusion Model to Generate Synthetic Datasets of Echocardiography Images

  Cristiana Tiago, Sten Roar Snare, Jurica Sprem, Kristin McLeod

• Membership Inference Attacks and Privacy in Topic Modeling

  Nico Manzonelli, Wanrong Zhang, Salil Vadhan

• Automatic and Universal Prompt Injection Attacks against Large Language Models

  Xiaogeng Liu, Zhiyuan Yu, Yizhe Zhang, Ning Zhang, Chaowei Xiao

2024-03-06

• Do You Trust Your Model? Emerging Malware Threats in the Deep Learning Ecosystem

  Dorjan Hitaj, Giulio Pagnotta, Fabio De Gaspari, Sediola Ruko, Briland Hitaj, Luigi V. Mancini, Fernando Perez-Cruz

• Adversarial Infrared Geometry: Using Geometry to Perform Adversarial Attack against Infrared Pedestrian Detectors

  Kalibinuer Tiliwalidi

• Advancing Out-of-Distribution Detection through Data Purification and Dynamic Activation Function Design

  Yingrui Ji, Yao Zhu, Zhigang Li, Jiansheng Chen, Yunlong Kong, Jingbo Chen

• Probing the Robustness of Time-series Forecasting Models with CounterfacTS

  Håkon Hanisch Kjærnli, Lluis Mas-Ribas, Aida Ashrafi, Gleb Sizov, Helge Langseth, Odd Erik Gundersen

• Learning Adversarial MDPs with Stochastic Hard Constraints

  Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

• Verified Training for Counterfactual Explanation Robustness under Data Shift

  Anna P. Meyer, Yuhao Zhang, Aws Albarghouthi, Loris D'Antoni

• DeepEclipse: How to Break White-Box DNN-Watermarking Schemes

  Alessandro Pegoraro, Carlotta Segna, Kavita Kumari, Ahmad-Reza Sadeghi

• Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

  Dario Pasquini, Martin Strohmeier, Carmela Troncoso

• Unsupervised Contrastive Learning for Robust RF Device Fingerprinting Under Time-Domain Shift

  Jun Chen, Weng-Keen Wong, Bechir Hamdaoui

• Improving Adversarial Training using Vulnerability-Aware Perturbation Budget

  Olukorede Fakorede, Modeste Atsague, Jin Tian

• Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability

  Rajdeep Haldar, Yue Xing, Qifan Song

• Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations

  Xiaolin Sun, Zizhan Zheng

• Fooling Neural Networks for Motion Forecasting via Adversarial Attacks

  Edgar Medina, Leyong Loh

2024-03-05

• FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models

  Younghan Lee, Yungi Cho, Woorim Han, Ho Bae, Yunheung Paek

• Recall-Oriented Continual Learning with Generative Adversarial Meta-Model

  Haneol Kang, Dong-Wan Choi

• Towards Robust Federated Learning via Logits Calibration on Non-IID Data

  Yu Qiao, Apurba Adhikary, Chaoning Zhang, Choong Seon Hong

• XAI-Based Detection of Adversarial Attacks on Deepfake Detectors

  Ben Pinhasov, Raz Lapid, Rony Ohayon, Moshe Sipper, Yehudit Aperstein

• Here Comes The AI Worm: Unleashing Zero-click Worms that Target GenAI-Powered Applications

  Stav Cohen, Ron Bitton, Ben Nassi

• Enhancing Security in Federated Learning through Adaptive Consensus-Based Model Update Validation

  Zahir Alsulaimawi

2024-03-03

• GuardT2I: Defending Text-to-Image Models from Adversarial Prompts

  Yijun Yang, Ruiyuan Gao, Xiao Yang, Jianyuan Zhong, Qiang Xu

• Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models

  Arijit Ghosh Chowdhury, Md Mofijul Islam, Vaibhav Kumar, Faysal Hossain Shezan, Vaibhav Kumar, Vinija Jain, Aman Chadha

2024-03-02

• Query Recovery from Easy to Hard: Jigsaw Attack against SSE

  Hao Nie, Wei Wang, Peng Xu, Xianglong Zhang, Laurence T. Yang, Kaitai Liang

• AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks

  Yifan Zeng, Yiran Wu, Xiao Zhang, Huazheng Wang, Qingyun Wu

2024-03-01

• AXOLOTL: Fairness through Assisted Self-Debiasing of Large Language Model Outputs

  Sana Ebrahimi, Kaiwen Chen, Abolfazl Asudeh, Gautam Das, Nick Koudas

• Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey

  Lucas Schott, Josephine Delas, Hatem Hajri, Elies Gherbi, Reda Yaich, Nora Boulahia-Cuppens, Frederic Cuppens, Sylvain Lamprier

• DPP-Based Adversarial Prompt Searching for Lanugage Models

  Xu Zhang, Xiaojun Wan

• Robustifying a Policy in Multi-Agent RL with Diverse Cooperative Behavior and Adversarial Style Sampling for Assistive Tasks

  Tayuki Osa, Tatsuya Harada

• Attacking Delay-based PUFs with Minimal Adversary Model

  Hongming Fei, Owen Millwood, Prosanta Gope, Jack Miskelly, Biplab Sikdar

2024-02-29

• Differentially Private Worst-group Risk Minimization

  Xinyu Zhou, Raef Bassily

• Utilizing Local Hierarchy with Adversarial Training for Hierarchical Text Classification

  Zihan Wang, Peiyi Wang, Houfeng Wang

• MPAT: Building Robust Deep Neural Networks against Textual Adversarial Attacks

  Fangyuan Zhang, Huichi Zhou, Shuangjiao Li, Hongtao Wang

• PRSA: Prompt Reverse Stealing Attacks against Large Language Models

  Yong Yang, Xuhong Zhang, Yi Jiang, Xi Chen, Haoyu Wang, Shouling Ji, Zonghui Wang

• Unraveling Adversarial Examples against Speaker Identification -- Techniques for Attack Detection and Victim Model Classification

  Sonal Joshi, Thomas Thebaud, Jesús Villalba, Najim Dehak

• Syntactic Ghost: An Imperceptible General-purpose Backdoor Attacks on Pre-trained Language Models

  Pengzhou Cheng, Wei Du, Zongru Wu, Fengwei Zhang, Libo Chen, Gongshen Liu

• Watermark Stealing in Large Language Models

  Nikola Jovanović, Robin Staab, Martin Vechev

• PrivatEyes: Appearance-based Gaze Estimation Using Federated Secure Multi-Party Computation

  Mayar Elfares, Pascal Reisert, Zhiming Hu, Wenwu Tang, Ralf Küsters, Andreas Bulling

• Typographic Attacks in Large Multimodal Models Can be Alleviated by More Informative Prompts

  Hao Cheng, Erjia Xiao, Renjing Xu

• Assessing Visually-Continuous Corruption Robustness of Neural Networks Relative to Human Performance

  Huakun Shen, Boyue Caroline Hu, Krzysztof Czarnecki, Lina Marsso, Marsha Chechik

• Verification of Neural Networks' Global Robustness

  Anan Kabaha, Dana Drachsler-Cohen

• Whispers that Shake Foundations: Analyzing and Mitigating False Premise Hallucinations in Large Language Models

  Hongbang Yuan, Pengfei Cao, Zhuoran Jin, Yubo Chen, Daojian Zeng, Kang Liu, Jun Zhao

• Pointing out the Shortcomings of Relation Extraction Models with Semantically Motivated Adversarials

  Gennaro Nolano, Moritz Blum, Basil Ell, Philipp Cimiano

• LoRA-as-an-Attack! Piercing LLM Safety Under The Share-and-Play Scenario

  Hongyi Liu, Zirui Liu, Ruixiang Tang, Jiayi Yuan, Shaochen Zhong, Yu-Neng Chuang, Li Li, Rui Chen, Xia Hu

2024-02-28

• Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

  Tong Liu, Yingjie Zhang, Zhe Zhao, Yinpeng Dong, Guozhu Meng, Kai Chen

• Enhancing Tracking Robustness with Auxiliary Adversarial Defense Networks

  Zhewei Wu, Ruilong Yu, Qihe Liu, Shuying Cheng, Shilin Qiu, Shijie Zhou

• Catastrophic Overfitting: A Potential Blessing in Disguise

  Mengnan Zhao, Lihe Zhang, Yuqiu Kong, Baocai Yin

• A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems

  Fangzhou Wu, Ning Zhang, Somesh Jha, Patrick McDaniel, Chaowei Xiao

• Unveiling Privacy, Memorization, and Input Curvature Links

  Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi, Kaushik Roy

• Model Pairing Using Embedding Translation for Backdoor Attack Detection on Open-Set Classification Tasks

  Alexander Unnervik, Hatef Otroshi Shahreza, Anjith George, Sébastien Marcel

• Pre-training Differentially Private Models with Limited Public Data

  Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis

• Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective

  Xinjian Luo, Yangfan Jiang, Fei Wei, Yuncheng Wu, Xiaokui Xiao, Beng Chin Ooi

2024-02-27

• Speak Out of Turn: Safety Vulnerability of Large Language Models in Multi-turn Dialogue

  Zhenhong Zhou, Jiuyang Xiang, Haopeng Chen, Quan Liu, Zherui Li, Sen Su

• FairBelief - Assessing Harmful Beliefs in Language Models

  Mattia Setzu, Marta Marchiori Manerba, Pasquale Minervini, Debora Nozza

• Extreme Miscalibration and the Illusion of Adversarial Robustness

  Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis

• Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain

  Qunliang Xing, Mai Xu, Shengxi Li, Xin Deng, Meisong Zheng, Huaida Liu, Ying Chen

• Preserving Fairness Generalization in Deepfake Detection

  Li Lin, Xinan He, Yan Ju, Xin Wang, Feng Ding, Shu Hu

• Black-box Adversarial Attacks Against Image Quality Assessment Models

  Yu Ran, Ao-Xiang Zhang, Mingjie Li, Weixuan Tang, Yuan-Gen Wang

• Structure-Guided Adversarial Training of Diffusion Models

  Ling Yang, Haotian Qian, Zhilong Zhang, Jingwei Liu, Bin Cui

• Towards Fairness-Aware Adversarial Learning

  Yanghao Zhang, Tianle Zhang, Ronghui Mu, Xiaowei Huang, Wenjie Ruan

• Model X-ray:Detect Backdoored Models via Decision Boundary

  Yanghao Su, Jie Zhang, Ting Xu, Tianwei Zhang, Weiming Zhang, Nenghai Yu

• Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates

  Daniele Angioni, Luca Demetrio, Maura Pintor, Luca Oneto, Davide Anguita, Battista Biggio, Fabio Roli

• Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple Sclerosis

  Lorenzo Peracchio, Giovanna Nicora, Enea Parimbelli, Tommaso Mario Buonocore, Roberto Bergamaschi, Eleonora Tavazzi, Arianna Dagliati, Riccardo Bellazzi

• LLM-Resistant Math Word Problem Generation via Adversarial Attacks

  Roy Xie, Chengxuan Huang, Junlin Wang, Bhuwan Dhingra

• Adversarial example soups: averaging multiple adversarial examples improves transferability without increasing additional generation time

  Bo Yang, Hengwei Zhang, Chenwei Li, Jindong Wang

2024-02-26

• Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion

  Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao

• Investigating Deep Watermark Security: An Adversarial Transferability Perspective

  Biqing Qi, Junqi Gao, Yiang Luo, Jianxing Liu, Ligang Wu, Bowen Zhou

• Training Implicit Generative Models via an Invariant Statistical Loss

  José Manuel de Frutos, Pablo M. Olmos, Manuel A. Vázquez, Joaquín Míguez

• CodeChameleon: Personalized Encryption Framework for Jailbreaking Large Language Models

  Huijie Lv, Xiao Wang, Yuansen Zhang, Caishuang Huang, Shihan Dou, Junjie Ye, Tao Gui, Qi Zhang, Xuanjing Huang

• Immunization against harmful fine-tuning attacks

  Domenic Rosati, Jan Wehner, Kai Williams, Łukasz Bartoszcze, Jan Batzner, Hassan Sajjad, Frank Rudzicz

• RoCoIns: Enhancing Robustness of Large Language Models through Code-Style Instructions

  Yuansen Zhang, Xiao Wang, Zhiheng Xi, Han Xia, Tao Gui, Qi Zhang, Xuanjing Huang

• ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors

  Zhexin Zhang, Yida Lu, Jingyuan Ma, Di Zhang, Rui Li, Pei Ke, Hao Sun, Lei Sha, Zhifang Sui, Hongning Wang, Minlie Huang

• Unveiling Vulnerability of Self-Attention

  Khai Jiet Liong, Hongqiu Wu, Hai Zhao

• Edge Detectors Can Make Deep Convolutional Neural Networks More Robust

  Jin Ding, Jie-Chao Zhao, Yong-Zhi Sun, Ping Tan, Jia-Wei Wang, Ji-En Ma, You-Tong Fang

• Improving the JPEG-resistance of Adversarial Attacks on Face Recognition by Interpolation Smoothing

  Kefu Guo, Fengfan Zhou, Hefei Ling, Ping Li, Hui Liu

• On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem

  Georg Pichler, Marco Romanelli, Divya Prakash Manivannan, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg

• A Curious Case of Remarkable Resilience to Gradient Attacks via Fully Convolutional and Differentiable Front End with a Skip Connection

  Leonid Boytsov, Ameya Joshi, Filipe Condessa

2024-02-25

• From Noise to Clarity: Unraveling the Adversarial Suffix of Large Language Model Attacks via Translation of Text Embeddings

  Hao Wang, Hao Li, Minlie Huang, Lei Sha

• Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing

  Jiabao Ji, Bairu Hou, Alexander Robey, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang

• Adversarial-Robust Transfer Learning for Medical Imaging via Domain Assimilation

  Xiaohui Chen, Tie Luo

• DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

  Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh

2024-02-24

• LLMs Can Defend Themselves Against Jailbreaking in a Practical Manner: A Vision Paper

  Daoyuan Wu, Shuai Wang, Yang Liu, Ning Liu

• RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation

  Jiawei Zhou, Linye Lyu, Daojing He, Yu Li

2024-02-23

• On the Duality Between Sharpness-Aware Minimization and Adversarial Training

  Yihao Zhang, Hangzhou He, Jingyu Zhu, Huanran Chen, Yifei Wang, Zeming Wei

• ProTIP: Probabilistic Robustness Verification on Text-to-Image Diffusion Models against Stochastic Perturbation

  Yi Zhang, Yun Tang, Wenjie Ruan, Xiaowei Huang, Siddartha Khastgir, Paul Jennings, Xingyu Zhao

• A First Look at GPT Apps: Landscape and Vulnerability

  Zejun Zhang, Li Zhang, Xin Yuan, Anlan Zhang, Mengwei Xu, Feng Qian

• Fast Adversarial Attacks on Language Models In One GPU Minute

  Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan, Priyatham Kattakinda, Atoosa Chegini, Soheil Feizi

• Distilling Adversarial Robustness Using Heterogeneous Teachers

  Jieren Deng, Aaron Palmer, Rigel Mahmood, Ethan Rathbun, Jinbo Bi, Kaleel Mahmood, Derek Aguiar

• Low-Frequency Black-Box Backdoor Attack via Evolutionary Algorithm

  Yanqi Qiao, Dazhuang Liu, Rui Wang, Kaitai Liang

• The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)

  Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang

2024-02-22

• Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off

  Futa Waseda, Isao Echizen

• Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfer

  Xinshuo Hu, Baotian Hu, Dongfang Li, Xiaoguang Li, Lifeng Shang

• Noise-BERT: A Unified Perturbation-Robust Framework with Noise Alignment Pre-training for Noisy Slot Filling Task

  Jinxu Zhao, Guanting Dong, Yueyan Qiu, Tingfeng Hui, Xiaoshuai Song, Daichi Guo, Weiran Xu

• Quadruplet Loss For Improving the Robustness to Face Morphing Attacks

  Iurii Medvedev, Nuno Gonçalves

• BeTAIL: Behavior Transformer Adversarial Imitation Learning from Human Racing Gameplay

  Catherine Weaver, Chen Tang, Ce Hao, Kenta Kawamoto, Masayoshi Tomizuka, Wei Zhan

• COBIAS: Contextual Reliability in Bias Assessment

  Priyanshul Govil, Vamshi Krishna Bonagiri, Manas Gaur, Ponnurangam Kumaraguru, Sanorita Dey

• Stop Reasoning! When Multimodal LLMs with Chain-of-Thought Reasoning Meets Adversarial Images

  Zefeng Wang, Zhen Han, Shuo Chen, Fan Xue, Zifeng Ding, Xun Xiao, Volker Tresp, Philip Torr, Jindong Gu

• Mitigating Fine-tuning Jailbreak Attack with Backdoor Enhanced Alignment

  Jiongxiao Wang, Jiazhao Li, Yiquan Li, Xiangyu Qi, Muhao Chen, Junjie Hu, Yixuan Li, Bo Li, Chaowei Xiao

• Mudjacking: Patching Backdoor Vulnerabilities in Foundation Models

  Hongbin Liu, Michael K. Reiter, Neil Zhenqiang Gong

• SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge

  Lucas Fenaux, Florian Kerschbaum

2024-02-21

• Large Language Models are Vulnerable to Bait-and-Switch Attacks for Generating Harmful Content

  Federico Bianchi, James Zou

• SDXL-Lightning: Progressive Adversarial Diffusion Distillation

  Shanchuan Lin, Anran Wang, Xiao Yang

• GradSafe: Detecting Unsafe Prompts for LLMs via Safety-Critical Gradient Analysis

  Yueqi Xie, Minghong Fang, Renjie Pi, Neil Gong

• Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment

  Vyas Raina, Adian Liusie, Mark Gales

• Learning to Poison Large Language Models During Instruction Tuning

  Yao Qiang, Xiangyu Zhou, Saleh Zare Zade, Mohammad Amin Roshani, Douglas Zytko, Dongxiao Zhu

• Coercing LLMs to do and reveal (almost) anything

  Jonas Geiping, Alex Stein, Manli Shu, Khalid Saifullah, Yuxin Wen, Tom Goldstein

• Robustness of Deep Neural Networks for Micro-Doppler Radar Classification

  Mikolaj Czerkawski, Carmine Clemente, Craig MichieCraig Michie, Christos Tachtatzis

• VL-Trojan: Multimodal Instruction Backdoor Attacks against Autoregressive Visual Language Models

  Jiawei Liang, Siyuan Liang, Man Luo, Aishan Liu, Dongchen Han, Ee-Chien Chang, Xiaochun Cao

• Stealthy Adversarial Attacks on Stochastic Multi-Armed Bandits

  Zhiwei Wang, Huazheng Wang, Hongning Wang

• AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning

  Vasudev Gohil, Satwik Patnaik, Dileep Kalathil, Jeyavijayan Rajendran

• Uncertainty-driven and Adversarial Calibration Learning for Epicardial Adipose Tissue Segmentation

  Kai Zhao, Zhiming Liu, Jiaqi Liu, Jingbiao Zhou, Bihong Liao, Huifang Tang, Qiuyu Wang, Chunquan Li

• Fake Resume Attacks: Data Poisoning on Online Job Platforms

  Michiharu Yamashita, Thanh Tran, Dongwon Lee

• Semantic Mirror Jailbreak: Genetic Algorithm Based Jailbreak Prompts Against Open-source LLMs

  Xiaoxia Li, Siyuan Liang, Jiyi Zhang, Han Fang, Aishan Liu, Ee-Chien Chang

2024-02-20

• TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification

  Martin Gubri, Dennis Ulmer, Hwaran Lee, Sangdoo Yun, Seong Joon Oh

• VGMShield: Mitigating Misuse of Video Generative Models

  Yan Pang, Yang Zhang, Tianhao Wang

• Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors

  Yiwei Lu, Matthew Y.R. Yang, Gautam Kamath, Yaoliang Yu

• Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies

  Xiangyu Liu, Chenghao Deng, Yanchao Sun, Yongyuan Liang, Furong Huang

• Defending Jailbreak Prompts via In-Context Adversarial Game

  Yujun Zhou, Yufei Han, Haomin Zhuang, Taicheng Guo, Kehan Guo, Zhenwen Liang, Hongyan Bao, Xiangliang Zhang

2024-02-19

• ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs

  Fengqing Jiang, Zhangchen Xu, Luyao Niu, Zhen Xiang, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran

• ChatGPT Based Data Augmentation for Improved Parameter-Efficient Debiasing of LLMs

  Pengrui Han, Rafal Kocielnik, Adhithya Saravanan, Roy Jiang, Or Sharir, Anima Anandkumar

• Acquiring Clean Language Models from Backdoor Poisoned Datasets by Downscaling Frequency Space

  Zongru Wu, Zhuosheng Zhang, Pengzhou Cheng, Gongshen Liu

• Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning

  Shuai Zhao, Leilei Gan, Luu Anh Tuan, Jie Fu, Lingjuan Lyu, Meihuizi Jia, Jinming Wen

• Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness

  Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen

• Query-Based Adversarial Prompt Generation

  Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr, Milad Nasr

• AICAttack: Adversarial Image Captioning Attack with Attention-Based Optimization

  Jiyao Li, Mingze Ni, Yifei Dong, Tianqing Zhu, Wei Liu

• Adversarial Feature Alignment: Balancing Robustness and Accuracy in Deep Learning via Adversarial Training

  Leo Hyun Park, Jaeuk Kim, Myung Gyo Oh, Jaewoo Park, Taekyoung Kwon

• Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models

  Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang

• Emulated Disalignment: Safety Alignment for Large Language Models May Backfire!

  Zhanhui Zhou, Jie Liu, Zhichen Dong, Jiaheng Liu, Chao Yang, Wanli Ouyang, Yu Qiao

• Attacks on Node Attributes in Graph Neural Networks

  Ying Xu, Michael Lanier, Anindya Sarkar, Yevgeniy Vorobeychik

2024-02-18

• How Susceptible are Large Language Models to Ideological Manipulation?

  Kai Chen, Zihao He, Jun Yan, Taiwei Shi, Kristina Lerman

• Stealthy Attack on Large Language Model based Recommendation

  Jinghao Zhang, Yuting Liu, Qiang Liu, Shu Wu, Guibing Guo, Liang Wang

2024-02-17

• Token-Ensemble Text Generation: On Attacking the Automatic AI-Generated Text Detection

  Fan Huang, Haewoon Kwak, Jisun An

• Maintaining Adversarial Robustness in Continuous Learning

  Xiaolei Ru, Xiaowei Cao, Zijia Liu, Jack Murdoch Moore, Xin-Ya Zhang, Xia Zhu, Wenjia Wei, Gang Yan

• Disclosure and Mitigation of Gender Bias in LLMs

  Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee

• A White-Box False Positive Adversarial Attack Method on Contrastive Loss Based Offline Handwritten Signature Verification Models

  Zhongliang Guo, Weiye Li, Yifei Qian, Ognjen Arandjelović, Lei Fang

2024-02-16

• Connect the dots: Dataset Condensation, Differential Privacy, and Adversarial Uncertainty

  Kenneth Odoh

• Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation

  Xinjian Zhao, Liang Zhang, Yang Liu, Ruocheng Guo, Xiangyu Zhao

• Zero-shot sampling of adversarial entities in biomedical question answering

  R. Patrick Xian, Alex J. Lee, Vincent Wang, Qiming Cui, Russell Ro, Reza Abbasi-Asl

• Universal Prompt Optimizer for Safe Text-to-Image Generation

  Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang

• Uncertainty, Calibration, and Membership Inference Attacks: An Information-Theoretic Perspective

  Meiyi Zhu, Caili Guo, Chunyan Feng, Osvaldo Simeone

• ASGEA: Exploiting Logic Rules from Align-Subgraphs for Entity Alignment

  Yangyifei Luo, Zhuo Chen, Lingbing Guo, Qian Li, Wenxuan Zeng, Zhixin Cai, Jianxin Li

• The Male CEO and the Female Assistant: Probing Gender Biases in Text-To-Image Models Through Paired Stereotype Test

  Yixin Wan, Kai-Wei Chang

• VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models

  Ziyi Yin, Muchao Ye, Tianrong Zhang, Jiaqi Wang, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma

• DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation

  Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva, Alexey Kurakin, Ibrahim Hammoud, Raman Arora

2024-02-15

• Generating Visual Stimuli from EEG Recordings using Transformer-encoder based EEG encoder and GAN

  Rahul Mishra, Arnav Bhavsar

• Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial Networks

  Joshua Park, Priyanshu Mahey, Ore Adeniyi

• Examining Pathological Bias in a Generative Adversarial Network Discriminator: A Case Study on a StyleGAN3 Model

  Alvin Grissom II, Ryan F. Lei, Jeova Farias Sales Rocha Neto, Bailey Lin, Ryan Trotter

• A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents

  Lingbo Mo, Zeyi Liao, Boyuan Zheng, Yu Su, Chaowei Xiao, Huan Sun

• Align before Attend: Aligning Visual and Textual Features for Multimodal Hateful Content Detection

  Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Sarah M. Preum

• Camouflage is all you need: Evaluating and Enhancing Language Model Robustness Against Camouflage Adversarial Attacks

  Álvaro Huertas-García, Alejandro Martín, Javier Huertas-Tato, David Camacho

• FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning

  Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos, Antonio Skarmeta

• Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention

  Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

• PAL: Proxy-Guided Black-Box Attack on Large Language Models

  Chawin Sitawarin, Norman Mu, David Wagner, Alexandre Araujo

• Reward Poisoning Attack Against Offline Reinforcement Learning

  Yinglun Xu, Rohan Gumaste, Gagandeep Singh

• AbuseGPT: Abuse of Generative AI ChatBots to Create Smishing Campaigns

  Ashfak Md Shibli, Mir Mehedi A. Pritom, Maanak Gupta

• Privacy Attacks in Decentralized Learning

  Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet

• How Much Does Each Datapoint Leak Your Privacy? Quantifying the Per-datum Membership Leakage

  Achraf Azize, Debabrota Basu

• A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents

  Lingbo Mo, Zeyi Liao, Boyuan Zheng, Yu Su, Chaowei Xiao, Huan Sun

• Camouflage is all you need: Evaluating and Enhancing Language Model Robustness Against Camouflage Adversarial Attacks

  Álvaro Huertas-García, Alejandro Martín, Javier Huertas-Tato, David Camacho

• Risk-Sensitive Soft Actor-Critic for Robust Deep Reinforcement Learning under Distribution Shifts

  Tobias Enders, James Harrison, Maximilian Schiffer

• How Much Does Each Datapoint Leak Your Privacy? Quantifying the Per-datum Membership Leakage

  Achraf Azize, Debabrota Basu

• Backdoor Attack against One-Class Sequential Anomaly Detection Models

  He Cheng, Shuhan Yuan

2024-02-14

• Exploring the Adversarial Capabilities of Large Language Models

  Lukas Struppek, Minh Hieu Le, Dominik Hintersdorf, Kristian Kersting

• Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models

  Weiheng Chai, Brian Testa, Huantao Ren, Asif Salekin, Senem Velipasalar

• Review-Incorporated Model-Agnostic Profile Injection Attacks on Recommender Systems

  Shiyi Yang, Lina Yao, Chen Wang, Xiwei Xu, Liming Zhu

• Attacking Large Language Models with Projected Gradient Descent

  Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Johannes Gasteiger, Stephan Günnemann

• Detecting Adversarial Spectrum Attacks via Distance to Decision Boundary Statistics

  Wenwei Zhao, Xiaowen Li, Shangqing Zhao, Jie Xu, Yao Liu, Zhuo Lu

• SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding

  Zhangchen Xu, Fengqing Jiang, Luyao Niu, Jinyuan Jia, Bill Yuchen Lin, Radha Poovendran

• Ten Words Only Still Help: Improving Black-Box AI-Generated Text Detection via Proxy-Guided Efficient Re-Sampling

  Yuhui Shi, Qiang Sheng, Juan Cao, Hao Mi, Beizhe Hu, Danding Wang

• Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption

  Chenlu Ye, Jiafan He, Quanquan Gu, Tong Zhang

• Play Guessing Game with LLM: Indirect Jailbreak Attack with Implicit Clues

  Zhiyuan Chang, Mingyang Li, Yi Liu, Junjie Wang, Qing Wang, Yang Liu

• Why Does Differential Privacy with Large Epsilon Defend Against Practical Membership Inference Attacks?

  Andrew Lowy, Zhuohang Li, Jing Liu, Toshiaki Koike-Akino, Kieran Parsons, Ye Wang

2024-02-13

• Data Reconstruction Attacks and Defenses: A Systematic Evaluation

  Sheng Liu, Zihan Wang, Qi Lei

• Faster Repeated Evasion Attacks in Tree Ensembles

  Lorenzo Cascioli, Laurens Devos, Ondřej Kuželka, Jesse Davis

• Generating Universal Adversarial Perturbations for Quantum Classifiers

  Gautham Anil, Vishnu Vinod, Apurva Narayan

• Enhancing Robustness of Indoor Robotic Navigation with Free-Space Segmentation Models Against Adversarial Attacks

  Qiyuan An, Christos Sevastopoulos, Fillia Makedon

• COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability

  Xingang Guo, Fangxu Yu, Huan Zhang, Lianhui Qin, Bin Hu

• Test-Time Backdoor Attacks on Multimodal Large Language Models

  Dong Lu, Tianyu Pang, Chao Du, Qian Liu, Xianjun Yang, Min Lin

• Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast

  Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, Min Lin

• Oracle-Efficient Differentially Private Learning with Public Data

  Adam Block, Mark Bun, Rathin Desai, Abhishek Shetty, Steven Wu

2024-02-12

• PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining

  Mishaal Kazmi, Hadrien Lautraite, Alireza Akbari, Mauricio Soroco, Qiaoyue Tang, Tao Wang, Sébastien Gambs, Mathias Lécuyer

• Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment

  Xabier Echeberria-Barrio, Amaia Gil-Lerchundi, Jon Egana-Zubia, Raul Orduna-Urrutia

• Topological safeguard for evasion attack interpreting the neural networks' behavior

  Xabier Echeberria-Barrio, Amaia Gil-Lerchundi, Iñigo Mendialdua, Raul Orduna-Urrutia

• PoisonedRAG: Knowledge Poisoning Attacks to Retrieval-Augmented Generation of Large Language Models

  Wei Zou, Runpeng Geng, Binghui Wang, Jinyuan Jia

• OrderBkd: Textual backdoor attack through repositioning

  Irina Alekseevskaia, Konstantin Arkhipenko

• Customizable Perturbation Synthesis for Robust SLAM Benchmarking

  Xiaohao Xu, Tianyi Zhang, Sibo Wang, Xiang Li, Yongqi Chen, Ye Li, Bhiksha Raj, Matthew Johnson-Roberson, Xiaonan Huang

• Multi-Attribute Vision Transformers are Efficient and Robust Learners

  Hanan Gani, Nada Saadi, Noor Hussein, Karthik Nandakumar

• Do Membership Inference Attacks Work on Large Language Models?

  Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min, Weijia Shi, Luke Zettlemoyer, Yulia Tsvetkov, Yejin Choi, David Evans, Hannaneh Hajishirzi

• NeuralSentinel: Safeguarding Neural Network Reliability and Trustworthiness

  Xabier Echeberria-Barrio, Mikel Gorricho, Selene Valencia, Francesco Zola

2024-02-11

• Accuracy of TextFooler black box adversarial attacks on 01 loss sign activation neural network ensemble

  Yunzhe Xue, Usman Roshan

• A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense

  Ryota Iijima, Sayaka Shiota, Hitoshi Kiya

2024-02-10

• Architectural Neural Backdoors from First Principles

  Harry Langford, Ilia Shumailov, Yiren Zhao, Robert Mullins, Nicolas Papernot

2024-02-09

• TETRIS: Towards Exploring the Robustness of Interactive Segmentation

  Andrey Moskalenko, Vlad Shakhuro, Anna Vorontsova, Anton Konushin, Anton Antonov, Alexander Krapukhin, Denis Shepelev, Konstantin Soshin

• RAMP: Boosting Adversarial Robustness Against Multiple lp Perturbations

  Enyi Jiang, Gagandeep Singh

• Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks

  Nandish Chattopadhyay, Amira Guesmi, Muhammad Shafique

• Evaluating Membership Inference Attacks and Defenses in Federated Learning

  Gongxi Zhu, Donghao Li, Hanlin Gu, Yuxing Han, Yuan Yao, Lixin Fan, Qiang Yang

• Studious Bob Fight Back Against Jailbreaking via Prompt Adversarial Tuning

  Yichuan Mo, Yuji Wang, Zeming Wei, Yisen Wang

• StruQ: Defending Against Prompt Injection with Structured Queries

  Sizhe Chen, Julien Piet, Chawin Sitawarin, David Wagner

• Quantifying and Enhancing Multi-modal Robustness with Modality Preference

  Zequn Yang, Yake Wei, Ce Liang, Di Hu

2024-02-08

• Reinforcement Learning as a Catalyst for Robust and Fair Federated Learning: Deciphering the Dynamics of Client Contributions

  Jialuo He, Wei Chen, Xiaojin Zhang

• Is Adversarial Training with Compressed Datasets Effective?

  Tong Chen, Raghavendra Selvan

• Investigating White-Box Attacks for On-Device Models

  Mingyi Zhou, Xiang Gao, Jing Wu, Kui Liu, Hailong Sun, Li Li

• Comprehensive Assessment of Jailbreak Attacks Against LLMs

  Junjie Chu, Yugeng Liu, Ziqing Yang, Xinyue Shen, Michael Backes, Yang Zhang

• Savvy: Trustworthy Autonomous Vehicles Architecture

  Ali Shoker, Rehana Yasmin, Paulo Esteves-Verissimo

2024-02-07

• InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory

  Chaojun Xiao, Pengle Zhang, Xu Han, Guangxuan Xiao, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Song Han, Maosong Sun

• Adversarial Robustness Through Artifact Design

  Tsufit Shua, Mahmood Sharif

• Group Distributionally Robust Dataset Distillation with Risk Minimization

  Saeed Vahidian, Mingyu Wang, Jianyang Gu, Vyacheslav Kungurtsev, Wei Jiang, Yiran Chen

• EvoSeed: Unveiling the Threat on Deep Neural Networks with Real-World Illusions

  Shashank Kotyan, PoYuan Mao, Danilo Vasconcellos Vargas

• SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models

  Lijun Li, Bowen Dong, Ruohui Wang, Xuhao Hu, Wangmeng Zuo, Dahua Lin, Yu Qiao, Jing Shao

• Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models

  Chirag Agarwal, Sree Harsha Tanneru, Himabindu Lakkaraju

• Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation

  Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod, An Tang, Guy Cloutier, Guy Wolf, Michael Eickenberg, Eugene Belilovsky

• De-amplifying Bias from Differential Privacy in Language Model Fine-tuning

  Sanjari Srivastava, Piotr Mardziel, Zhikhun Zhang, Archana Ahlawat, Anupam Datta, John C Mitchell

2024-02-06

• Partially Recentralization Softmax Loss for Vision-Language Models Robustness

  Hao Wang, Xin Zhang, Jinzhe Jiang, Yaqian Zhao, Chen Li

• A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective

  Lei Yu, Meng Han, Yiming Li, Changting Lin, Yao Zhang, Mingyang Zhang, Yan Liu, Haiqin Weng, Yuseok Jeon, Ka-Ho Chow, Stacy Patterson

• Boosting Adversarial Transferability across Model Genus by Deformation-Constrained Warping

  Qinliang Lin, Cheng Luo, Zenghao Niu, Xilin He, Weicheng Xie, Yuanbo Hou, Linlin Shen, Siyang Song

• Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science

  Xiangru Tang, Qiao Jin, Kunlun Zhu, Tongxin Yuan, Yichi Zhang, Wangchunshu Zhou, Meng Qu, Yilun Zhao, Jian Tang, Zhuosheng Zhang, Arman Cohan, Zhiyong Lu, Mark Gerstein

• HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

  Mantas Mazeika, Long Phan, Xuwang Yin, Andy Zou, Zifan Wang, Norman Mu, Elham Sakhaee, Nathaniel Li, Steven Basart, Bo Li, David Forsyth, Dan Hendrycks

• Measuring Implicit Bias in Explicitly Unbiased Large Language Models

  Xuechunzi Bai, Angelina Wang, Ilia Sucholutsky, Thomas L. Griffiths

• Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

  Hao Fang, Yixiang Qiu, Hongyao Yu, Wenbo Yu, Jiawei Kong, Baoli Chong, Bin Chen, Xuan Wang, Shu-Tao Xia

• Fairness and Privacy Guarantees in Federated Contextual Bandits

  Sambhav Solanki, Shweta Jain, Sujit Gujar

• PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network

  Tan Sun, Junhong Lin

• Towards Fair, Robust and Efficient Client Contribution Evaluation in Federated Learning

  Meiying Zhang, Huan Zhao, Sheldon Ebron, Kan Yang

• PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection

  Enyan Dai, Minhua Lin, Suhang Wang

• Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning

  Sarwar Khan

2024-02-05

• Exploiting Class Probabilities for Black-box Sentence-level Attacks

  Raha Moraffah, Huan Liu

• A Generative Approach to Surrogate-based Black-box Attacks

  Raha Moraffah, Huan Liu

• Evading Data Contamination Detection for Language Models is (too) Easy

  Jasper Dekoninck, Mark Niklas Müller, Maximilian Baader, Marc Fischer, Martin Vechev

• Homograph Attacks on Maghreb Sentiment Analyzers

  Fatima Zahra Qachfar, Rakesh M. Verma

• Conversation Reconstruction Attack Against GPT Models

  Junjie Chu, Zeyang Sha, Michael Backes, Yang Zhang

• GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models

  Haibo Jin, Ruoxi Chen, Andy Zhou, Jinyin Chen, Yang Zhang, Haohan Wang

• Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics

  Shuai Li, Xiaoyu Jiang, Xiaoguang Ma

• DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models

  Yang Sui, Huy Phan, Jinqi Xiao, Tianfang Zhang, Zijie Tang, Cong Shi, Yan Wang, Yingying Chen, Bo Yuan

• Time-Distributed Backdoor Attacks on Federated Spiking Learning

  Gorka Abad, Stjepan Picek, Aitor Urbieta

• Adversarial Data Augmentation for Robust Speaker Verification

  Zhenyu Zhou, Junhui Chen, Namin Wang, Lantian Li, Dong Wang

• Arabic Synonym BERT-based Adversarial Examples for Text Classification

  Norah Alshahrani, Saied Alshahrani, Esma Wali, Jeanna Matthews

• Generalization Properties of Adversarial Training for $\ell_0$-Bounded Adversarial Attacks

  Payam Delgosha, Hamed Hassani, Ramtin Pedarsani

2024-02-04

• DeSparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision Transformers

  Oryan Yehezkel, Alon Zolfi, Amit Baras, Yuval Elovici, Asaf Shabtai

• PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks

  Ziquan Liu, Zhuo Zhi, Ilija Bogunovic, Carsten Gerner-Beuerle, Miguel Rodrigues

2024-02-03

• Seeing is not always believing: The Space of Harmless Perturbations

  Lu Chen, Shaofeng Li, Benhao Huang, Fan Yang, Zheng Li, Jie Li, Yuan Luo

• Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error

  Haoran Li, Zicheng Zhang, Wang Luo, Congying Han, Yudong Hu, Tiande Guo, Shichen Liao

• Rethinking the Starting Point: Enhancing Performance and Fairness of Federated Learning via Collaborative Pre-Training

  Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher G. Brinton

• Data Poisoning for In-context Learning

  Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang

• Universal Post-Training Reverse-Engineering Defense Against Backdoors in Deep Neural Networks

  Xi Li, Hang Wang, David J. Miller, George Kesidis

• MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers

  Yatong Bai, Mo Zhou, Vishal M. Patel, Somayeh Sojoudi

2024-02-02

• Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance

  Wenqi Wei, Ling Liu

• STAA-Net: A Sparse and Transferable Adversarial Attack for Speech Emotion Recognition

  Yi Chang, Zhao Ren, Zixing Zhang, Xin Jing, Kun Qian, Xi Shao, Bin Hu, Tanja Schultz, Björn W. Schuller

• Delving into Decision-based Black-box Attacks on Semantic Segmentation

  Zhaoyu Chen, Zhengyang Shan, Jingwen Chang, Kaixun Jiang, Dingkang Yang, Yiting Cheng, Wenqiang Zhang

• Synthetic Data for the Mitigation of Demographic Biases in Face Recognition

  Pietro Melzi, Christian Rathgeb, Ruben Tolosana, Ruben Vera-Rodriguez, Aythami Morales, Dominik Lawatsch, Florian Domin, Maxim Schaubert

• Cheating Suffix: Targeted Attack to Text-To-Image Diffusion Models with Multi-Modal Priors

  Dingcheng Yang, Yang Bai, Xiaojun Jia, Yang Liu, Xiaochun Cao, Wenjian Yu

• SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding

  Chanho Park, Namyoon Lee

• On the Transferability of Large-Scale Self-Supervision to Few-Shot Audio Classification

  Calum Heggan, Sam Budgett, Timothy Hosepedales, Mehrdad Yeghoobi

• $σ$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples

  Antonio Emanuele Cinà, Francesco Villani, Maura Pintor, Lea Schönherr, Battista Biggio, Marcello Pelillo

• Position Paper: Assessing Robustness, Privacy, and Fairness in Federated Learning Integrated with Foundation Models

  Xi Li, Jiaqi Wang

• HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text

  Han Liu, Zhi Xu, Xiaotong Zhang, Feng Zhang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang

• Preference Poisoning Attacks on Reward Model Learning

  Junlin Wu, Jiongxiao Wang, Chaowei Xiao, Chenguang Wang, Ning Zhang, Yevgeniy Vorobeychik

• SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization

  Xixu Hu, Runkai Zheng, Jindong Wang, Cheuk Hang Leung, Qi Wu, Xing Xie

2024-02-01

• Hidding the Ghostwriters: An Adversarial Evaluation of AI-Generated Student Essay Detection

  Xinlin Peng, Ying Zhou, Ben He, Le Sun, Yingfei Sun

• Safety of Multimodal Large Language Models on Images and Text

  Xin Liu, Yichen Zhu, Yunshi Lan, Chao Yang, Yu Qiao

• Masked Conditional Diffusion Model for Enhancing Deepfake Detection

  Tiewen Chen, Shanmin Yang, Shu Hu, Zhenghan Fang, Ying Fu, Xi Wu, Xin Wang

• Vision-LLMs Can Fool Themselves with Self-Generated Typographic Attacks

  Maan Qraitem, Nazia Tasnim, Kate Saenko, Bryan A. Plummer

• Approximating Optimal Morphing Attacks using Template Inversion

  Laurent Colbois, Hatef Otroshi Shahreza, Sébastien Marcel

• Tropical Decision Boundaries for Neural Networks Are Robust Against Adversarial Attacks

  Kurt Pasque, Christopher Teska, Ruriko Yoshida, Keiji Miura, Jefferson Huang

• Short: Benchmarking Transferable Adversarial Attacks

  Zhibo Jin, Jiayu Zhang, Zhiyu Zhu, Huaming Chen

• Large Language Models Based Fuzzing Techniques: A Survey

  Linghan Huang, Peizhou Zhao, Huaming Chen, Lei Ma

• Investigating Bias Representations in Llama 2 Chat via Activation Steering

  Dawn Lu, Nina Rimsky

• Invariance-powered Trustworthy Defense via Remove Then Restore

  Xiaowei Fu, Yuhang Zhou, Lina Ma, Lei Zhang

• Safety of Multimodal Large Language Models on Images and Text

  Xin Liu, Yichen Zhu, Yunshi Lan, Chao Yang, Yu Qiao

• Vision-LLMs Can Fool Themselves with Self-Generated Typographic Attacks

  Maan Qraitem, Nazia Tasnim, Kate Saenko, Bryan A. Plummer

• Survey of Privacy Threats and Countermeasures in Federated Learning

  Masahiro Hayashitani, Junki Mori, Isamu Teranishi

• FairEHR-CLP: Towards Fairness-Aware Clinical Predictions with Contrastive Learning in Multimodal Electronic Health Records

  Yuqing Wang, Malvika Pillai, Yun Zhao, Catherine Curtin, Tina Hernandez-Boussard

• BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion Attacks

  Hamed Poursiami, Ihsen Alouani, Maryam Parsa

2024-01-31

• Manipulating Predictions over Discrete Inputs in Machine Teaching

  Xiaodong Wu, Yufei Han, Hayssam Dahrouj, Jianbing Ni, Zhenwen Liang, Xiangliang Zhang

• Unified Physical-Digital Face Attack Detection

  Hao Fang, Ajian Liu, Haocheng Yuan, Junze Zheng, Dingheng Zeng, Yanhong Liu, Jiankang Deng, Sergio Escalera, Xiaoming Liu, Jun Wan, Zhen Lei

• Logit Poisoning Attack in Distillation-based Federated Learning and its Countermeasures

  Yonghao Yu, Shunan Zhu, Jinglu Hu

• Adversarial Quantum Machine Learning: An Information-Theoretic Generalization Analysis

  Petros Georgiou, Sharu Theresa Jose, Osvaldo Simeone

• Common Sense Reasoning for Deep Fake Detection

  Yue Zhang, Ben Colman, Ali Shahriyari, Gaurav Bharaj

• Privacy and Security Implications of Cloud-Based AI Services : A Survey

  Alka Luqman, Riya Mahesh, Anupam Chattopadhyay

• An Early Categorization of Prompt Injection Attacks on Large Language Models

  Sippo Rossi, Alisia Marianne Michel, Raghava Rao Mukkamala, Jason Bennett Thatcher

2024-01-30

• Detection and Recovery Against Deep Neural Network Fault Injection Attacks Based on Contrastive Learning

  Chenan Wang, Pu Zhao, Siyue Wang, Xue Lin

• Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate

  Steffi Chern, Ethan Chern, Graham Neubig, Pengfei Liu

• Finetuning Large Language Models for Vulnerability Detection

  Alexey Shestov, Anton Cheshkov, Rodion Levichev, Ravil Mussabayev, Pavel Zadorozhny, Evgeny Maslov, Chibirev Vadim, Egor Bulychev

• Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks

  Andy Zhou, Bo Li, Haohan Wang

• Gradient-Based Language Model Red Teaming

  Nevan Wichers, Carson Denison, Ahmad Beirami

• Single Word Change is All You Need: Designing Attacks and Defenses for Text Classifiers

  Lei Xu, Sarah Alnegheimish, Laure Berti-Equille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni

• Weak-to-Strong Jailbreaking on Large Language Models

  Xuandong Zhao, Xianjun Yang, Tianyu Pang, Chao Du, Lei Li, Yu-Xiang Wang, William Yang Wang

• Optimal-Landmark-Guided Image Blending for Face Morphing Attacks

  Qiaoyun He, Zongyong Deng, Zuyuan He, Qijun Zhao

• Towards Assessing the Synthetic-to-Measured Adversarial Vulnerability of SAR ATR

  Bowen Peng, Bo Peng, Jingyuan Xia, Tianpeng Liu, Yongxiang Liu, Li Liu

• Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks

  Lulu Xue, Shengshan Hu, Ruizhi Zhao, Leo Yu Zhang, Shengqing Hu, Lichao Sun, Dezhong Yao

• Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems

  Mohammed Elnawawy, Mohammadreza Hallajiyan, Gargi Mitra, Shahrear Iqbal, Karthik Pattabiraman

• Provably Robust Multi-bit Watermarking for AI-generated Text via Error Correction Code

  Wenjie Qu, Dong Yin, Zixin He, Wei Zou, Tianyang Tao, Jinyuan Jia, Jiaheng Zhang

• AdvGPS: Adversarial GPS for Multi-Agent Perception Attack

  Jinlong Li, Baolu Li, Xinyu Liu, Jianwu Fang, Felix Juefei-Xu, Qing Guo, Hongkai Yu

• Security and Privacy Challenges of Large Language Models: A Survey

  Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu

• Large Language Models in Cybersecurity: State-of-the-Art

  Farzad Nourmohammadzadeh Motlagh, Mehrdad Hajizadeh, Mehryar Majd, Pejman Najafi, Feng Cheng, Christoph Meinel

2024-01-29

• Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization

  Guang Lin, Chao Li, Jianhai Zhang, Toshihisa Tanaka, Qibin Zhao

• Finding Challenging Metaphors that Confuse Pretrained Language Models

  Yucheng Li, Frank Guerin, Chenghua Lin

• Transparency Attacks: How Imperceptible Image Layers Can Fool AI Perception

  Forrest McKee, David Noever

• TransTroj: Transferable Backdoor Attacks to Pre-trained Models via Embedding Indistinguishability

  Hao Wang, Tao Xiang, Shangwei Guo, Jialing He, Hangcheng Liu, Tianwei Zhang

• AdvNF: Reducing Mode Collapse in Conditional Normalising Flows using Adversarial Learning

  Vikas Kanaujia, Mathias S. Scheurer, Vipul Arora

• Red-Teaming for Generative AI: Silver Bullet or Security Theater?

  Michael Feffer, Anusha Sinha, Zachary C. Lipton, Hoda Heidari

• LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection

  Jiwei Tian, Chao Shen, Buhong Wang, Xiaofang Xia, Meng Zhang, Chenhao Lin, Qian Li

• Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters

  Shahed Masoudian, Cornelia Volaucnik, Markus Schedl, Shahed Masoudian

2024-01-28

• Lips Are Lying: Spotting the Temporal Inconsistency between Audio and Visual in Lip-Syncing DeepFakes

  Weifeng Liu, Tianyi She, Jiawei Liu, Run Wang, Dongyu Yao, Ziyou Liang

• Addressing Noise and Efficiency Issues in Graph-Based Machine Learning Models From the Perspective of Adversarial Attack

  Yongyu Wang

• Integrating Differential Privacy and Contextual Integrity

  Sebastian Benthall, Rachel Cummings

2024-01-27

• L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks

  Ping Guo, Fei Liu, Xi Lin, Qingchuan Zhao, Qingfu Zhang

• Style-News: Incorporating Stylized News Generation and Adversarial Verification for Neural Fake News Detection

  Wei-Yao Wang, Yu-Chieh Chang, Wen-Chih Peng

• Multi-Trigger Backdoor Attacks: More Triggers, More Threats

  Yige Li, Xingjun Ma, Jiabo He, Hanxun Huang, Yu-Gang Jiang

• Asymptotic Behavior of Adversarial Training Estimator under $\ell_\infty$-Perturbation

  Yiling Xie, Xiaoming Huo

2024-01-26

• Mitigating Feature Gap for Adversarial Robustness by Feature Disentanglement

  Nuoyan Zhou, Dawei Zhou, Decheng Liu, Xinbo Gao, Nannan Wang

• Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training

  Shruthi Gowda, Bahram Zonooz, Elahe Arani

• BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning

  Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu, Shaokui Wei, Danni Yuan, Mingli Zhu, Ruotong Wang, Li Liu, Chao Shen

• Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings

  Dmytro Zakharov, Oleksandr Kuznetsov, Emanuele Frontoni

• GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption

  Eugene Frimpong, Khoa Nguyen, Mindaugas Budzys, Tanveer Khan, Antonis Michalas

• PrivStream: An Algorithm for Streaming Differentially Private Data

  Girish Kumar, Thomas Strohmer, Roman Vershynin

• Coca: Improving and Explaining Graph Neural Network-Based Vulnerability Detection Systems

  Sicong Cao, Xiaobing Sun, Xiaoxue Wu, David Lo, Lili Bo, Bin Li, Wei Liu

• Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective

  Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng

• MEA-Defender: A Robust Watermark against Model Extraction Attack

  Peizhuo Lv, Hualong Ma, Kai Chen, Jiachen Zhou, Shengzhi Zhang, Ruigang Liang, Shenchen Zhu, Pan Li, Yingjun Zhang

2024-01-25

• Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation

  Yifan Yang, Xiaoyu Liu, Qiao Jin, Furong Huang, Zhiyong Lu

• Adaptive Text Watermark for Large Language Models

  Yepeng Liu, Yuheng Bu

• Sparse and Transferable Universal Singular Vectors Attack

  Kseniia Kuvshinova, Olga Tsymboi, Ivan Oseledets

• The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Out-of-Distribution Robustness

  Mengyao Du, Miao Zhang, Yuwen Pu, Kai Xu, Shouling Ji, Quanjun Yin

• Information Leakage Detection through Approximate Bayes-optimal Prediction

  Pritha Gupta, Marcel Wever, Eyke Hüllermeier

• Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization

  Adnan Khan, Mai A. Shaaban, Muhammad Haris Khan

• Producing Plankton Classifiers that are Robust to Dataset Shift

  Cheng Chen, Sreenath Kyathanahally, Marta Reyes, Stefanie Merkli, Ewa Merz, Emanuele Francazi, Marvin Hoege, Francesco Pomati, Marco Baity-Jesi

• Decentralized Federated Learning: A Survey on Security and Privacy

  Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif, Boyu Wang, Qiang Yang

2024-01-24

• Boosting the Transferability of Adversarial Examples via Local Mixup and Adaptive Step Size

  Junlin Liu, Xinchen Lyu

• AdCorDA: Classifier Refinement via Adversarial Correction and Domain Adaptation

  Lulan Shen, Ali Edalati, Brett Meyer, Warren Gross, James J. Clark

• Multi-Agent Diagnostics for Robustness via Illuminated Diversity

  Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel

• Can overfitted deep neural networks in adversarial training generalize? -- An approximation viewpoint

  Zhongjie Shi, Fanghui Liu, Yuan Cao, Johan A.K. Suykens

• A Systematic Approach to Robustness Modelling for Deep Convolutional Neural Networks

  Charles Meyers, Mohammad Reza Saleh Sedghpour, Tommy Löfstedt, Erik Elmroth

• Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning

  Andrea Apicella, Francesco Isgrò, Roberto Prevete

• LAA-Net: Localized Artifact Attention Network for High-Quality Deepfakes Detection

  Dat Nguyen, Nesryne Mejri, Inder Pal Singh, Polina Kuleshova, Marcella Astrid, Anis Kacem, Enjie Ghorbel, Djamila Aouada

• Inference Attacks Against Face Recognition Model without Classification Layers

  Yuanqing Huang, Huilong Chen, Yinggui Wang, Lei Wang

• A Systematic Approach to Robustness Modelling for Deep Convolutional Neural Networks

  Charles Meyers, Mohammad Reza Saleh Sedghpour, Tommy Löfstedt, Erik Elmroth

2024-01-23

• Securing Recommender System via Cooperative Training

  Qingyang Wang, Chenwang Wu, Defu Lian, Enhong Chen

• DAFA: Distance-Aware Fair Adversarial Training

  Hyungyu Lee, Saehyung Lee, Hyemi Jang, Junsung Park, Ho Bae, Sungroh Yoon

• Fast Adversarial Training against Textual Adversarial Attacks

  Yichen Yang, Xin Liu, Kun He

• MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage

  Ying Song, Balaji Palanisamy

• ToDA: Target-oriented Diffusion Attacker against Recommendation System

  Xiaohao Liu, Zhulin Tao, Ting Jiang, He Chang, Yunshan Ma, Xianglin Huang

• Digital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems

  Michelle R. Greene, Mariam Josyula, Wentao Si, Jennifer A. Hart

• The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts

  Lingfeng Shen, Weiting Tan, Sihao Chen, Yunmo Chen, Jingyu Zhang, Haoran Xu, Boyuan Zheng, Philipp Koehn, Daniel Khashabi

2024-01-22

• GI-PIP: Do We Require Impractical Auxiliary Dataset for Gradient Inversion Attacks?

  Yu sun, Gaojian Xiong, Xianxun Yao, Kailang Ma, Jian Cui

• Safe and Generalized end-to-end Autonomous Driving System with Reinforcement Learning and Demonstrations

  Zuojin Tang, Xiaoyu Chen, YongQiang Li, Jianyu Chen

• Robustness to distribution shifts of compressed networks for edge devices

  Lulan Shen, Ali Edalati, Brett Meyer, Warren Gross, James J. Clark

• Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

  Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein

• Text Embedding Inversion Attacks on Multilingual Language Models

  Yiyi Chen, Heather Lent, Johannes Bjerva

• A Training-Free Defense Framework for Robust Learned Image Compression

  Myungseo Song, Jinyoung Choi, Bohyung Han

• Privacy-Preserving Data Fusion for Traffic State Estimation: A Vertical Federated Learning Approach

  Qiqing Wang, Kaidi Yang

• Analyzing the Quality Attributes of AI Vision Models in Open Repositories Under Adversarial Attacks

  Zerui Wang, Yan Liu

• GRATH: Gradual Self-Truthifying for Large Language Models

  Weixin Chen, Bo Li

2024-01-21

• Finding a Needle in the Adversarial Haystack: A Targeted Paraphrasing Approach For Uncovering Edge Cases with Minimal Distribution Distortion

  Aly M. Kassem, Sherif Saad

• Adversarial Augmentation Training Makes Action Recognition Models More Robust to Realistic Video Distribution Shifts

  Kiyoon Kim, Shreyank N Gowda, Panagiotis Eustratiadis, Antreas Antoniou, Robert B Fisher

• TetraLoss: Improving the Robustness of Face Recognition against Morphing Attacks

  Mathias Ibsen, Lázaro J. González-Soler, Christian Rathgeb, Christoph Busch

• How Robust Are Energy-Based Models Trained With Equilibrium Propagation?

  Siddharth Mansingh, Michal Kucer, Garrett Kenyon, Juston Moore, Michael Teti

2024-01-20

• CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications

  Hangsheng Zhang, Jiqiang Liu, Jinsong Dong

• BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models

  Zhen Xiang, Fengqing Jiang, Zidi Xiong, Bhaskar Ramasubramanian, Radha Poovendran, Bo Li

2024-01-19

• PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks

  Ping Guo, Zhiyuan Yang, Xi Lin, Qingchuan Zhao, Qingfu Zhang

• Pruning for Protection: Increasing Jailbreak Resistance in Aligned LLMs Without Fine-Tuning

  Adib Hasan, Ileana Rugina, Alex Wang

• Mitigating Hallucinations of Large Language Models via Knowledge Consistent Alignment

  Fanqi Wan, Xinting Huang, Leyang Cui, Xiaojun Quan, Wei Bi, Shuming Shi

• Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation

  Janvi Thakkar, Giulio Zizzo, Sergio Maffeis

• Adversarially Robust Signed Graph Contrastive Learning from Balance Augmentation

  Jialong Zhou, Xing Ai, Yuni Lai, Kai Zhou

• Hacking Predictors Means Hacking Cars: Using Sensitivity Analysis to Identify Trajectory Prediction Vulnerabilities for Autonomous Driving Security

  Marsalis Gibson, David Babazadeh, Claire Tomlin, Shankar Sastry

• A Lightweight Multi-Attack CAN Intrusion Detection System on Hybrid FPGAs

  Shashwat Khandelwal, Shreejith Shanker

• Real-Time Zero-Day Intrusion Detection System for Automotive Controller Area Network on FPGAs

  Shashwat Khandelwal, Shreejith Shanker

• The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness

  Yifan Hao, Tong Zhang

2024-01-18

• Uncertainty-Aware Hardware Trojan Detection Using Multimodal Deep Learning

  Rahul Vishwakarma, Amin Rezaei

• Power in Numbers: Robust reading comprehension by finetuning with four adversarial sentences per example

  Ariel Marcus

• Marrying Adapters and Mixup to Efficiently Enhance the Adversarial Robustness of Pre-Trained Language Models for Text Classification

  Tuc Nguyen, Thai Le

• Artwork Protection Against Neural Style Transfer Using Locally Adaptive Adversarial Color Attack

  Zhongliang Guo, Kaixuan Wang, Weiye Li, Yifei Qian, Ognjen Arandjelović, Lei Fang

• Cross-Modality Perturbation Synergy Attack for Person Re-identification

  Yunpeng Gong, others

• MedBlindTuner: Towards Privacy-preserving Fine-tuning on Biomedical Images with Transformers and Fully Homomorphic Encryption

  Prajwal Panzade, Daniel Takabi, Zhipeng Cai

• MITS-GAN: Safeguarding Medical Imaging from Tampering with Generative Adversarial Networks

  Giovanni Pasqualino, Luca Guarnera, Alessandro Ortis, Sebastiano Battiato

• Universally Robust Graph Neural Networks by Preserving Neighbor Similarity

  Yulin Zhu, Yuni Lai, Xing Ai, Kai Zhou

• HGAttack: Transferable Heterogeneous Graph Adversarial Attack

  He Zhao, Zhiwei Zeng, Yongwei Wang, Deheng Ye, Chunyan Miao

• Hijacking Attacks against Neural Networks by Analyzing Training Data

  Yunjie Ge, Qian Wang, Huayang Huang, Qi Li, Cong Wang, Chao Shen, Lingchen Zhao, Peipei Jiang, Zheng Fang, Shenyi Zhang

2024-01-17

• MITS-GAN: Safeguarding Medical Imaging from Tampering with Generative Adversarial Networks

  Giovanni Pasqualino, Luca Guarnera, Alessandro Ortis, Sebastiano Battiato

• An Optimal Transport Approach for Computing Adversarial Training Lower Bounds in Multiclass Classification

  Nicolas Garcia Trillos, Matt Jacobs, Jakwang Kim, Matthew Werenski

• Artwork Protection Against Neural Style Transfer Using Locally Adaptive Adversarial Color Attack

  Zhongliang Guo, Kaixuan Wang, Weiye Li, Yifei Qian, Ognjen Arandjelović, Lei Fang

2024-01-16

• Bag of Tricks to Boost Adversarial Transferability

  Zeliang Zhang, Rongyi Zhu, Wei Yao, Xiaosen Wang, Chenliang Xu

• Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning

  Yu Jiang, Jiyuan Shen, Ziyao Liu, Chee Wei Tan, Kwok-Yan Lam

• PPR: Enhancing Dodging Attacks while Maintaining Impersonation Attacks on Face Recognition Systems

  Fengfan Zhou, Heifei Ling

• A Generative Adversarial Attack for Multilingual Text Classifiers

  Tom Roth, Inigo Jauregi Unanue, Alsharif Abuadbba, Massimo Piccardi

2024-01-15

• Left-right Discrepancy for Adversarial Attack on Stereo Networks

  Pengfei Wang, Xiaofei Hui, Beijia Lu, Nimrod Lilith, Jun Liu, Sameer Alam

• Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability

  Junxi Chen, Junhao Dong, Xiaohua Xie

• Crafter: Facial Feature Crafting against Inversion-based Identity Theft on Deep Models

  Shiming Wang, Zhe Ji, Liyao Xiang, Hao Zhang, Xinbing Wang, Chenghu Zhou, Bo Li

• Robustness Against Adversarial Attacks via Learning Confined Adversarial Polytopes

  Shayan Mohajer Hamidi; Linfeng Ye

2024-01-12

• An Analytical Framework for Modeling and Synthesizing Malicious Attacks on ACC Vehicles

  Shian Wang

• Adversarial Examples are Misaligned in Diffusion Model Manifolds

  Peter Lorenz, Ricard Durall, Janis Keuper

• How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs

  Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, Weiyan Shi

2024-01-11

• Combating Adversarial Attacks with Multi-Agent Debate

  Steffi Chern, Zhen Fan, Andy Liu

• GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model

  Zhiyu Zhu, Huaming Chen, Xinyi Wang, Jiayu Zhang, Zhibo Jin, Kim-Kwang Raymond Choo

• Universal Vulnerabilities in Large Language Models: In-context Learning Backdoor Attacks

  Shuai Zhao, Meihuizi Jia, Luu Anh Tuan, Jinming Wen

• Can We Trust the Unlabeled Target Data? Towards Backdoor Attack and Defense on Model Adaptation

  Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

2024-01-10

• Revisiting Adversarial Training at Scale

  Zeyu Wang, Xianhang Li, Hongru Zhu, Cihang Xie

• SoK: Facial Deepfake Detectors

  Binh M. Le, Jiwon Kim, Shahroz Tariq, Kristen Moore, Alsharif Abuadbba, Simon S. Woo

• Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

  Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, Ethan Perez

• TrustLLM: Trustworthiness in Large Language Models

  Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, Willian Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

• Exploring Vulnerabilities of No-Reference Image Quality Assessment Models: A Query-Based Black-Box Method

  Chenxi Yang, Yujia Liu, Dingquan Li, Tingting Jiang

2024-01-09

• Deep Anomaly Detection in Text

  Andrei Manolache

• Human as AI Mentor: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving

  Zilin Huang, Zihao Sheng, Chengyuan Ma, Sikai Chen

• An Investigation of Large Language Models for Real-World Hate Speech Detection

  Keyan Guo, Alexander Hu, Jaden Mu, Ziheng Shi, Ziming Zhao, Nishant Vishwamitra, Hongxin Hu

• LLM-Powered Code Vulnerability Repair with Reinforcement Learning and Semantic Reward

  Nafis Tanveer Islam, Joseph Khoury, Andrew Seong, Gonzalo De La Torre Parra, Elias Bou-Harb, Peyman Najafirad

• GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning

  Syed Irfan Ali Meerza, Luyang Liu, Jiaxin Zhang, Jian Liu

• Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs

  Pengfei Ding, Yan Wang, Guanfeng Liu, Nan Wang

• A Large-scale Empirical Study on Improving the Fairness of Deep Learning Models

  Junjie Yang, Jiajun Jiang, Zeyu Sun, Junjie Chen

• The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performance

  Abel Salinas, Fred Morstatter

• Transferable Learned Image Compression-Resistant Adversarial Perturbations

  Yang Sui, Zhuohang Li, Ding Ding, Xiang Pan, Xiaozhong Xu, Shan Liu, Zhenzhong Chen

• Adaptive Boosting with Fairness-aware Reweighting Technique for Fair Classification

  Xiaobin Song, Zeyuan Liu, Benben Jiang

• Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks

  Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

2024-01-08

• Logits Poisoning Attack in Federated Distillation

  Yuhan Tang, Zhiyuan Wu, Bo Gao, Tian Wen, Yuwei Wang, Sheng Sun

2024-01-07

• Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception

  Takami Sato, Sri Hrushikesh Varma Bhupathiraju, Michael Clifford, Takeshi Sugawara, Qi Alfred Chen, Sara Rampazzi

• Data-Driven Subsampling in the Presence of an Adversarial Actor

  Abu Shafin Mohammad Mahdee Jameel, Ahmed P. Mohamed, Jinho Yi, Aly El Gamal, Akshay Malhotra

• ROIC-DM: Robust Text Inference and Classification via Diffusion Model

  Shilong Yuan, Wei Yuan, Tieke HE

2024-01-06

• Data-Dependent Stability Analysis of Adversarial Training

  Yihan Wang, Shuang Liu, Xiao-Shan Gao

• End-to-End Anti-Backdoor Learning on Images and Time Series

  Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, Yige Li, James Bailey

2024-01-05

• Transferable Learned Image Compression-Resistant Adversarial Perturbations

  Yang Sui, Zhuohang Li, Ding Ding, Xiang Pan, Xiaozhong Xu, Shan Liu, Zhenzhong Chen

• Enhancing targeted transferability via feature space fine-tuning

  Hui Zeng, Biwei Chen, Anjie Peng

• Calibration Attack: A Framework For Adversarial Attacks Targeting Calibration

  Stephen Obadinma, Xiaodan Zhu, Hongyu Guo

• A backdoor attack against link prediction tasks with graph neural networks

  Jiazhu Dai, Haoyu Sun

• MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance

  Renjie Pi, Tianyang Han, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang

2024-01-04

• Vulnerabilities Unveiled: Adversarially Attacking a Multimodal Vision Langauge Model for Pathology Imaging

  Jai Prakash Veerla, Poojitha Thota, Partha Sai Guttikonda, Shirin Nilizadeh, Jacob M. Luber

• A Random Ensemble of Encrypted models for Enhancing Robustness against Adversarial Examples

  Ryota Iijima, Sayaka Shiota, Hitoshi Kiya

• AdvSQLi: Generating Adversarial SQL Injections against Real-world WAF-as-a-service

  Zhenqing Qu, Xiang Ling, Ting Wang, Xiang Chen, Shouling Ji, Chunming Wu

• Evasive Hardware Trojan through Adversarial Power Trace

  Behnam Omidi, Khaled N. Khasawneh, Ihsen Alouani

• Object-oriented backdoor attack against image captioning

  Meiling Li, Nan Zhong, Xinpeng Zhang, Zhenxing Qian, Sheng Li

• DEM: A Method for Certifying Deep Neural Network Classifier Outputs in Aerospace

  Guy Katz, Natan Levy, Idan Refaeli, Raz Yerushalmi

• Secure Control of Connected and Automated Vehicles Using Trust-Aware Robust Event-Triggered Control Barrier Functions

  H M Sabbir Ahmad, Ehsan Sabouni, Akua Dickson, Wei Xiao, Christos G. Cassandras, Wenchao Li

2024-01-03

• Towards Robust Semantic Segmentation against Patch-based Attack via Attention Refinement

  Zheng Yuan, Jie Zhang, Yude Wang, Shiguang Shan, Xilin Chen

• Spy-Watermark: Robust Invisible Watermarking for Backdoor Attack

  Ruofei Wang, Renjie Wan, Zongyu Guo, Qing Guo, Rui Huang

• FullLoRA-AT: Efficiently Boosting the Robustness of Pretrained Vision Transformers

  Zheng Yuan, Jie Zhang, Shiguang Shan

• Integrated Cyber-Physical Resiliency for Power Grids under IoT-Enabled Dynamic Botnet Attacks

  Yuhan Zhao, Juntao Chen, Quanyan Zhu

• Enhancing Generalization of Invisible Facial Privacy Cloak via Gradient Accumulation

  Xuannan Liu, Yaoyao Zhong, Weihong Deng, Hongzhi Shi, Xingchen Cui, Yunfeng Yin, Dongchao Wen

2024-01-02

• Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment

  Jie Zhu, Leye Wang, Xiao Han, Anmin Liu, Tao Xie

• Teach Large Language Models to Forget Privacy

  Ran Yan, Yujun Li, Wenqian Li, Peihua Mai, Yan Pang, Yinchuan Li

• PPBFL: A Privacy Protected Blockchain-based Federated Learning Model

  Yang Li, Chunhe Xia, Wanshuang Lin, Tianbo Wang

• LLbezpeky: Leveraging Large Language Models for Vulnerability Detection

  Noble Saji Mathews, Yelizaveta Brus, Yousra Aafer, Mei Nagappan, Shane McIntosh

• Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise

  Qinglong Huang, Yong Liao, Yanbin Hao, Pengyuan Zhou

• Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control

  Ka-Ho Chow, Wenqi Wei, Lei Yu

• Efficient Sparse Least Absolute Deviation Regression with Differential Privacy

  Weidong Liu, Xiaojun Mao, Xiaofei Zhang, Xin Zhang

• Opening A Pandora's Box: Things You Should Know in the Era of Custom GPTs

  Guanhong Tao, Siyuan Cheng, Zhuo Zhang, Junmin Zhu, Guangyu Shen, Xiangyu Zhang

• A Novel Evaluation Framework for Assessing Resilience Against Prompt Injection Attacks in Large Language Models

  Daniel Wankit Yip, Aysan Esmradi, Chun Fai Chan

• Detection and Defense Against Prominent Attacks on Preconditioned LLM-Integrated Virtual Assistants

  Chun Fai Chan, Daniel Wankit Yip, Aysan Esmradi

2024-01-01

• Red Teaming for Large Language Models At Scale: Tackling Hallucinations on Mathematics Tasks

  Aleksander Buszydlik, Karol Dobiczek, Michał Teodor Okoń, Konrad Skublicki, Philip Lippmann, Jie Yang

• A & B == B & A: Triggering Logical Reasoning Failures in Large Language Models

  Yuxuan Wan, Wenxuan Wang, Yiliu Yang, Youliang Yuan, Jen-tse Huang, Pinjia He, Wenxiang Jiao, Michael R. Lyu

• SHARE: Single-view Human Adversarial REconstruction

  Shreelekha Revankar, Shijia Liao, Yu Shen, Junbang Liang, Huaishu Peng, Ming Lin

• SSL-OTA: Unveiling Backdoor Threats in Self-Supervised Learning for Object Detection

  Qiannan Wang, Changchun Yin, Liming Fang, Lu Zhou, Zhe Liu, Run Wang, Chenhao Lin

• Adversarially Trained Actor Critic for offline CMDPs

  Honghao Wei, Xiyue Peng, Xin Liu, Arnob Ghosh

2023-12-31

• Is It Possible to Backdoor Face Forgery Detection with Natural Triggers

  Xiaoxuan Han, Songlin Yang, Wei Wang, Ziwen He, Jing Dong

2023-12-30

• Explainability-Driven Leaf Disease Classification using Adversarial Training and Knowledge Distillation

  Sebastian-Vasile Echim, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel, Florin Pop

• CamPro: Camera-based Anti-Facial Recognition

  Wenjun Zhu, Yuan Sun, Jiani Liu, Yushi Cheng, Xiaoyu Ji, Wenyuan Xu

• TPatch: A Triggered Physical Adversarial Patch

  Wenjun Zhu, Xiaoyu Ji, Yushi Cheng, Shibo Zhang, Wenyuan Xu

• A clean-label graph backdoor attack method in node classification task

  Xiaogang Xing, Ming Xu, Yujing Bai, Dongdong Yang

2023-12-29

• Jatmo: Prompt Injection Defense by Task-Specific Finetuning

  Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, David Wagner

• Towards Faithful Explanations for Text Classification with Robustness Improvement and Explanation Guided Training

  Dongfang Li, Baotian Hu, Qingcai Chen, Shan He

2023-12-28

• Layer Attack Unlearning: Fast and Accurate Machine Unlearning via Layer Level Attack and Knowledge Distillation

  Hyunjune Kim, Sangyong Lee, Simon S. Woo

• Adversarial Representation with Intra-Modal and Inter-Modal Graph Contrastive Learning for Multimodal Emotion Recognition

  Yuntao Shou, Tao Meng, Wei Ai, Keqin Li

• SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning

  Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

• Adversarial Attacks on Image Classification Models: Analysis and Defense

  Jaydip Sen, Abhiraj Sen, Ananda Chatterjee

• BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks

  Meixi Zheng, Xuanchen Yan, Zihao Zhu, Hongrui Chen, Baoyuan Wu

• Attack Tree Analysis for Adversarial Evasion Attacks

  Yuki Yamaguchi, Toshiaki Aoki

• DOEPatch: Dynamically Optimized Ensemble Model for Adversarial Patches Generation

  Wenyi Tan, Yang Li, Chenxing Zhao, Zhunga Liu, Quan Pan

• Securing NextG Systems against Poisoning Attacks on Federated Learning: A Game-Theoretic Solution

  Yalin E. Sagduyu, Tugba Erpek, Yi Shi

• Timeliness: A New Design Metric and a New Attack Surface

  Priyanka Kaswan, Sennur Ulukus

2023-12-27

• Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It

  Federico Siciliano, Luca Maiano, Lorenzo Papa, Federica Baccin, Irene Amerini, Fabrizio Silvestri

• Adversarial Attacks on LoRa Device Identification and Rogue Signal Detection with Deep Learning

  Yalin E. Sagduyu, Tugba Erpek

• Domain Generalization with Vital Phase Augmentation

  Ingyun Lee, Wooju Lee, Hyun Myung

2023-12-26

• From Text to Multimodal: A Comprehensive Survey of Adversarial Example Generation in Question Answering Systems

  Gulsum Yigit, Mehmet Fatih Amasyali

• Natural Adversarial Patch Generation Method Based on Latent Diffusion Model

  Xianyi Chen, Fazhan Liu, Dong Jiang, Kai Yan

• Universal Pyramid Adversarial Training for Improved ViT Performance

  Ping-yeh Chiang, Yipin Zhou, Omid Poursaeed, Satya Narayan Shukla, Ashish Shah, Tom Goldstein, Ser-Nam Lim

• Robust Survival Analysis with Adversarial Regularization

  Michael Potter, Stefano Maxenti, Michael Everett

2023-12-25

• GanFinger: GAN-Based Fingerprint Generation for Deep Neural Network Ownership Verification

  Huali Ren, Anli Yan, Xiaojun Ren, Pei-Gen Ye, Chong-zhi Gao, Zhili Zhou, Jin Li

• Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion

  Lijian Chen, Wei Yuan, Tong Chen, Quoc Viet Hung Nguyen, Lizhen Cui, Hongzhi Yin

• Punctuation Matters! Stealthy Backdoor Attack for Language Models

  Xuan Sheng, Zhicheng Li, Zhaoyang Han, Xiangmao Chang, Piji Li

2023-12-24

• Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models

  Jingwei Yi, Yueqi Xie, Bin Zhu, Keegan Hines, Emre Kiciman, Guangzhong Sun, Xing Xie, Fangzhao Wu

• Hierarchical Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks

  Taha Eghtesad, Sirui Li, Yevgeniy Vorobeychik, Aron Laszka

• AutoAugment Input Transformation for Highly Transferable Targeted Attacks

  Haobo Lu, Xin Liu, Kun He

• Can Machines Learn Robustly, Privately, and Efficiently?

  Youssef Allouah, Rachid Guerraoui, John Stephan

2023-12-23

• Adversarial Data Poisoning for Fake News Detection: How to Make a Model Misclassify a Target News without Modifying It

  Federico Siciliano, Luca Maiano, Lorenzo Papa, Federica Baccin, Irene Amerini, Fabrizio Silvestri

• Pre-trained Trojan Attacks for Visual Recognition

  Aishan Liu, Xinwei Zhang, Yisong Xiao, Yuguang Zhou, Siyuan Liang, Jiakai Wang, Xianglong Liu, Xiaochun Cao, Dacheng Tao

2023-12-22

• MEAOD: Model Extraction Attack against Object Detectors

  Zeyu Li, Chenghui Shi, Yuwen Pu, Xuhong Zhang, Yu Li, Jinbao Li, Shouling Ji

• Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks

  Haz Sameen Shahgir, Xianghao Kong, Greg Ver Steeg, Yue Dong

• Understanding the Regularity of Self-Attention with Optimal Transport

  Valérie Castin, Pierre Ablin, Gabriel Peyré

• Attacking Byzantine Robust Aggregation in High Dimensions

  Sarthak Choudhary, Aashish Kolluri, Prateek Saxena

• SODA: Protecting Proprietary Information in On-Device Machine Learning Models

  Akanksha Atrey, Ritwik Sinha, Saayan Mitra, Prashant Shenoy

• Energy-based learning algorithms for analog computing: a comparative study

  Benjamin Scellier, Maxence Ernoult, Jack Kendall, Suhas Kumar

• Adaptive Domain Inference Attack

  Yuechun Gu, Keke Chen

2023-12-21

• Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses

  Ilias Tsingenopoulos, Vera Rimmer, Davy Preuveneers, Fabio Pierazzi, Lorenzo Cavallaro, Wouter Joosen

• Using GPT-4 Prompts to Determine Whether Articles Contain Functional Evidence Supporting or Refuting Variant Pathogenicity

  Samuel J. Aronson, Kalotina Machini, Pranav Sriraman, Jiyeon Shin, Emma R. Henricks, Charlotte Mailly, Angie J. Nottage, Michael Oates, Matthew S. Lebo

• SADA: Semantic adversarial unsupervised domain adaptation for Temporal Action Localization

  David Pujol-Perich, Albert Clapés, Sergio Escalera

• ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks

  Peng Zhao, Jiehua Zhang, Bowen Peng, Longguang Wang, YingMei Wei, Yu Liu, Li Liu

• Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples

  Ruichu Cai, Yuxuan Zhu, Jie Qiao, Zefeng Liang, Furui Liu, Zhifeng Hao

• Manipulating Trajectory Prediction with Backdoors

  Kaouther Massoud, Kathrin Grosse, Mickael Chen, Matthieu Cord, Patrick Pérez, Alexandre Alahi

2023-12-20

• Progressive Poisoned Data Isolation for Training-time Backdoor Defense

  Yiming Chen, Haiwei Wu, Jiantao Zhou

• PGN: A perturbation generation network against deep reinforcement learning

  Xiangjuan Li, Feifan Li, Yang Li, Quan Pan

• Learning and Forgetting Unsafe Examples in Large Language Models

  Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren

• Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation

  Jiaming Liu, Ran Xu, Senqiao Yang, Renrui Zhang, Qizhe Zhang, Zehui Chen, Yandong Guo, Shanghang Zhang

• Misalign, Contrast then Distill: Rethinking Misalignments in Language-Image Pretraining

  Bumsoo Kim, Yeonsik Jo, Jinhyung Kim, Seung Hwan Kim

• Mutual-modality Adversarial Attack with Semantic Perturbation

  Jingwen Ye, Ruonan Yu, Songhua Liu, Xinchao Wang

• Trust, But Verify: A Survey of Randomized Smoothing Techniques

  Anupriya Kumari, Devansh Bhardwaj, Sukrit Jindal, Sarthak Gupta

• Stability of Graph Convolutional Neural Networks through the lens of small perturbation analysis

  Lucia Testa, Claudio Battiloro, Stefania Sardellitti, Sergio Barbarossa

• Neural Stochastic Differential Equations with Change Points: A Generative Adversarial Approach

  Zhongchang Sun, Yousef El-Laham, Svitlana Vyetrenko

• SkyMask: Attack-agnostic Robust Federated Learning with Fine-grained Learnable Masks

  Peishen Yan, Hao Wang, Tao Song, Yang Hua, Ruhui Ma, Ningxin Hu, Mohammad R. Haghighat, Haibing Guan

• Can Large Language Models Identify And Reason About Security Vulnerabilities? Not Yet

  Saad Ullah, Mingji Han, Saurabh Pujar, Hammond Pearce, Ayse Coskun, Gianluca Stringhini

2023-12-19

• A Red Teaming Framework for Securing AI in Maritime Autonomous Systems

  Mathew J. Walter, Aaron Barrett, Kimberly Tam

• Maatphor: Automated Variant Analysis for Prompt Injection Attacks

  Ahmed Salem, Andrew Paverd, Boris Köpf

• Robust Communicative Multi-Agent Reinforcement Learning with Active Defense

  Lebin Yu, Yunbo Qiu, Quanming Yao, Yuan Shen, Xudong Zhang, Jian Wang

• Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in ultra low-data regimes

  Nabeel Seedat, Nicolas Huynh, Boris van Breugel, Mihaela van der Schaar

• Bypassing the Safety Training of Open-Source LLMs with Priming Attacks

  Jason Vega, Isha Chaudhary, Changming Xu, Gagandeep Singh

• Chasing Fairness in Graphs: A GNN Architecture Perspective

  Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu

• Adversarial AutoMixup

  Huafeng Qin, Xin Jin, Yun Jiang, Mounim A. El-Yacoubi, Xinbo Gao

• Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Models

  Shweta Mahajan, Tanzila Rahman, Kwang Moo Yi, Leonid Sigal

• A Study on Transferability of Deep Learning Models for Network Intrusion Detection

  Shreya Ghosh, Abu Shafin Mohammad Mahdee Jameel, Aly El Gamal

• Android Malware Detection with Unbiased Confidence Guarantees

  Harris Papadopoulos, Nestoras Georgiou, Charalambos Eliades, Andreas Konstantinidis

• Terrapin Attack: Breaking SSH Channel Integrity By Sequence Number Manipulation

  Fabian Bäumer, Marcus Brinkmann, Jörg Schwenk

2023-12-18

• Annotation-Free Automatic Music Transcription with Scalable Synthetic Data and Adversarial Domain Confusion

  Gakusei Sato, Taketo Akama

• SAME: Sample Reconstruction Against Model Extraction Attacks

  Yi Xie, Jie Zhang, Shiqian Zhao, Tianwei Zhang, Xiaofeng Chen

• Synthesizing Black-box Anti-forensics DeepFakes with High Visual Quality

  Bing Fan, Shu Hu, Feng Ding

• Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach

  Faysal Mahmud, Yusha Abdullah, Minhajul Islam, Tahsin Aziz

• DataElixir: Purifying Poisoned Dataset to Mitigate Backdoor Attacks via Diffusion Models

  Jiachen Zhou, Peizhuo Lv, Yibing Lan, Guozhu Meng, Kai Chen, Hualong Ma

• Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion Model

  Decheng Liu, Xijun Wang, Chunlei Peng, Nannan Wang, Ruiming Hu, Xinbo Gao

• Bengali Intent Classification with Generative Adversarial BERT

  Mehedi Hasan, Mohammad Jahid Ibna Basher, Md. Tanvir Rouf Shawon

• Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off

  Yu-An Liu, Ruqing Zhang, Mingkun Zhang, Wei Chen, Maarten de Rijke, Jiafeng Guo, Xueqi Cheng

• Closing the Gap: Achieving Better Accuracy-Robustness Tradeoffs Against Query-Based Attacks

  Pascal Zimmer, Sébastien Andreina, Giorgia Azzurra Marson, Ghassan Karame

• Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability

  Jaehui Hwang, Junghyuk Lee, Jong-Seok Lee

• The Ultimate Combo: Boosting Adversarial Example Transferability by Composing Data Augmentations

  Zebin Yun, Achi-Or Weingarten, Eyal Ronen, Mahmood Sharif

• On Robustness to Missing Video for Audiovisual Speech Recognition

  Oscar Chang, Otavio Braga, Hank Liao, Dmitriy Serdyuk, Olivier Siohan

• Rethinking Robustness of Model Attributions

  Sandesh Kamath, Sankalp Mittal, Amit Deshpande, Vineeth N Balasubramanian

• The Pros and Cons of Adversarial Robustness

  Yacine Izza, Joao Marques-Silva

• PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning

  Yuting Ma, Yuanzhi Yao, Xiaohua Xu

• TrojFSP: Trojan Insertion in Few-shot Prompt Tuning

  Mengxin Zheng, Jiaqi Xue, Xun Chen, YanShan Wang, Qian Lou, Lei Jiang

• TrojFair: Trojan Fairness Attacks

  Mengxin Zheng, Jiaqi Xue, Yi Sheng, Lei Yang, Qian Lou, Lei Jiang

• Adversarially Balanced Representation for Continuous Treatment Effect Estimation

  Amirreza Kazemi, Martin Ester

• Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity

  Zhihao Zhu, Chenwang Wu, Rui Fan, Yi Yang, Defu Lian, Enhong Chen

• MISA: Unveiling the Vulnerabilities in Split Federated Learning

  Wei Wan, Yuxuan Ning, Shengshan Hu1, Lulu Xue, Minghui Li, Leo Yu Zhang, Hai Jin

• Uncertainty-based Fairness Measures

  Selim Kuzucu, Jiaee Cheong, Hatice Gunes, Sinan Kalkan

• Improving Environment Robustness of Deep Reinforcement Learning Approaches for Autonomous Racing Using Bayesian Optimization-based Curriculum Learning

  Rohan Banerjee, Prishita Ray, Mark Campbell

• Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning

  Keyi Ju, Xiaoqi Qin, Hui Zhong, Xinyue Zhang, Miao Pan, Baoling Liu

• UltraClean: A Simple Framework to Train Robust Neural Networks against Backdoor Attacks

  Bingyin Zhao, Yingjie Lao

• A Mutation-Based Method for Multi-Modal Jailbreaking Attack Detection

  Xiaoyu Zhang, Cen Zhang, Tianlin Li, Yihao Huang, Xiaojun Jia, Xiaofei Xie, Yang Liu, Chao Shen

• Federated learning with differential privacy and an untrusted aggregator

  Kunlong Liu, Trinabh Gupta

• A Comprehensive Survey of Attack Techniques, Implementation, and Mitigation Strategies in Large Language Models

  Aysan Esmradi, Daniel Wankit Yip, Chun Fai Chan

2023-12-17

• Investigating Responsible AI for Scientific Research: An Empirical Study

  Muneera Bano, Didar Zowghi, Pip Shea, Georgina Ibarra

• Continual Adversarial Defense

  Qian Wang, Yaoyao Liu, Hefei Ling, Yingwei Li, Qihao Liu, Ping Li, Jiazhong Chen, Alan Yuille, Ning Yu

• SlowTrack: Increasing the Latency of Camera-based Perception in Autonomous Driving Using Adversarial Examples

  Chen Ma, Ningfei Wang, Qi Alfred Chen, Chao Shen

• Embodied Adversarial Attack: A Dynamic Robust Physical Attack in Autonomous Driving

  Yitong Sun, Yao Huang, Xingxing Wei

• Adversarial Robustness on Image Classification with $k$-means

  Rollin Omari, Junae Kim, Paul Montague

• Fragility, Robustness and Antifragility in Deep Learning

  Chandresh Pravin, Ivan Martino, Giuseppe Nicosia, Varun Ojha

• Reliable Probabilistic Classification with Neural Networks

  Harris Papadopoulos

• A Malware Classification Survey on Adversarial Attacks and Defences

  Mahesh Datta Sai Ponnuru, Likhitha Amasala, Tanu Sree Bhimavarapu, Guna Chaitanya Garikipati

• Silent Guardian: Protecting Text from Malicious Exploitation by Large Language Models

  Jiawei Zhao, Kejiang Chen, Xiaojian Yuan, Yuang Qi, Weiming Zhang, Nenghai Yu

2023-12-16

• Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks

  Ao Liu, Wenshan Li, Tao Li, Beibei Li, Hanyuan Huang, Pan Zhou

2023-12-15

• PhasePerturbation: Speech Data Augmentation via Phase Perturbation for Automatic Speech Recognition

  Chengxi Lei, Satwinder Singh, Feng Hou, Xiaoyun Jia, Ruili Wang

• Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey

  Yichen Wan, Youyang Qu, Wei Ni, Yong Xiang, Longxiang Gao, Ekram Hossain

• The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation

  Rongwu Xu, Brian S. Lin, Shujian Yang, Tianqi Zhang, Weiyan Shi, Tianwei Zhang, Zhixuan Fang, Wei Xu, Han Qiu

• Privacy Constrained Fairness Estimation for Decision Trees

  Florian van der Steen, Fré Vink, Heysem Kaya

• Scalable Ensemble-based Detection Method against Adversarial Attacks for speaker verification

  Haibin Wu, Heng-Cheng Kuo, Yu Tsao, Hung-yi Lee

2023-12-14

• AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection

  Xiangtao Meng, Li Wang, Shanqing Guo, Lei Ju, Qingchuan Zhao

• On the Difficulty of Defending Contrastive Learning against Backdoor Attacks

  Changjiang Li, Ren Pang, Bochuan Cao, Zhaohan Xi, Jinghui Chen, Shouling Ji, Ting Wang

• Detection and Defense of Unlearnable Examples

  Yifan Zhu, Lijia Yu, Xiao-Shan Gao

• Improve Robustness of Reinforcement Learning against Observation Perturbations via $l_\infty$ Lipschitz Policy Networks

  Buqing Nie, Jingtian Ji, Yangqing Fu, Yue Gao

• Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey

  Yichen Wan, Youyang Qu, Wei Ni, Yong Xiang, Longxiang Gao, Ekram Hossain

• DRAM-Locker: A General-Purpose DRAM Protection Mechanism against Adversarial DNN Weight Attacks

  Ranyang Zhou, Sabbir Ahmed, Arman Roohi, Adnan Siraj Rakin, Shaahin Angizi

• Forbidden Facts: An Investigation of Competing Objectives in Llama-2

  Tony T. Wang, Miles Wang, Kaivu Hariharan, Nir Shavit

• Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret

  Adam Żychowski, Andrew Perrault, Jacek Mańdziuk

• Exploring Transferability for Randomized Smoothing

  Kai Qiu, Huishuai Zhang, Zhirong Wu, Stephen Lin

• Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting

  Anthony Chen, Huanrui Yang, Yulu Gan, Denis A Gudovskiy, Zhen Dong, Haofan Wang, Tomoyuki Okuno, Yohei Nakata, Shanghang Zhang, Kurt Keutzer

2023-12-13

• Defenses in Adversarial Machine Learning: A Survey

  Baoyuan Wu, Shaokui Wei, Mingli Zhu, Meixi Zheng, Zihao Zhu, Mingda Zhang, Hongrui Chen, Danni Yuan, Li Liu, Qingshan Liu

• Robust Few-Shot Named Entity Recognition with Boundary Discrimination and Correlation Purification

  Xiaojun Xue, Chunxia Zhang, Tianxiang Xu, Zhendong Niu

• Universal Adversarial Framework to Improve Adversarial Robustness for Diabetic Retinopathy Detection

  Samrat Mukherjee, Dibyanayan Bandyopadhyay, Baban Gain, Asif Ekbal

• Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks

  Ao Liu, Wenshan Li, Tao Li, Beibei Li, Hanyuan Huang, Pan Zhou

• Scalable Ensemble-based Detection Method against Adversarial Attacks for speaker verification

  Haibin Wu, Heng-Cheng Kuo, Yu Tsao, Hung-yi Lee

• Accelerating the Global Aggregation of Local Explanations

  Alon Mor, Yonatan Belinkov, Benny Kimelfeld

• Erasing Self-Supervised Learning Backdoor by Cluster Activation Masking

  Shengsheng Qian, Yifei Wang, Dizhan Xue, Shengjie Zhang, Huaiwen Zhang, Changsheng Xu

• Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models

  Jiang Zhang, Qiong Wu, Yiming Xu, Cheng Cao, Zheng Du, Konstantinos Psounis

2023-12-12

• Patch-MI: Enhancing Model Inversion Attacks via Patch-Based Reconstruction

  Jonggyu Jang, Hyeonsu Lyu, Hyun Jong Yang

• Radio Signal Classification by Adversarially Robust Quantum Machine Learning

  Yanqiu Wu, Eromanga Adermann, Chandra Thapa, Seyit Camtepe, Hajime Suzuki, Muhammad Usman

• SSTA: Salient Spatially Transformed Attack

  Renyang Liu, Wei Zhou, Sixin Wu, Jun Zhao, Kwok-Yan Lam

• DTA: Distribution Transform-based Attack for Query-Limited Scenario

  Renyang Liu, Wei Zhou, Xin Jin, Song Gao, Yuanyu Wang, Ruxin Wang

• May the Noise be with you: Adversarial Training without Adversarial Examples

  Ayoub Arous, Andres F Lopez-Lopera, Nael Abu-Ghazaleh, Ihsen Alouani

• Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training

  Qian Li, Yuxiao Hu, Yinpeng Dong, Dongxiao Zhang, Yuntian Chen

• Attacking the Loop: Adversarial Attacks on Graph-based Loop Closure Detection

  Jonathan J. Y. Kim, Martin Urschler, Patricia J. Riddle, Jorg S. Wicker

• Collapse-Oriented Adversarial Training with Triplet Decoupling for Robust Image Retrieval

  Qiwei Tian, Chenhao Lin, Qian Li, Zhengyu Zhao, Chao Shen

• ReRoGCRL: Representation-based Robustness in Goal-Conditioned Reinforcement Learning

  Xiangyu Yin, Sihao Wu, Jiaxu Liu, Meng Fang, Xingyu Zhao, Xiaowei Huang, Wenjie Ruan

• Robust MRI Reconstruction by Smoothed Unrollin

  Shijun Liang, Van Hoang Minh Nguyen, Jinghan Jia, Ismail Alkhouri, Sijia Liu, Saiprasad Ravishankar

• Cost Aware Untargeted Poisoning Attack against Graph Neural Networks,

  Yuwei Han, Yuni Lai, Yulin Zhu, Kai Zhou

• EdgePruner: Poisoned Edge Pruning in Graph Contrastive Learning

  Hiroya Kato, Kento Hasegawa, Seira Hidano, Kazuhide Fukushima

• Causality Analysis for Evaluating the Security of Large Language Models

  Wei Zhao, Zhe Li, Jun Sun

• SimAC: A Simple Anti-Customization Method against Text-to-Image Synthesis of Diffusion Models

  Feifei Wang, Zhentao Tan, Tianyi Wei, Yue Wu, Qidong Huang

• Eroding Trust In Aerial Imagery: Comprehensive Analysis and Evaluation Of Adversarial Attacks In Geospatial Systems

  Michael Lanier, Aayush Dhakal, Zhexiao Xiong, Arthur Li, Nathan Jacobs, Yevgeniy Vorobeychik

• Securing Graph Neural Networks in MLaaS: A Comprehensive Realization of Query-based Integrity Verification

  Bang Wu, Xingliang Yuan, Shuo Wang, Qi Li, Minhui Xue, Shirui Pan

• Majority is Not Required: A Rational Analysis of the Private Double-Spend Attack from a Sub-Majority Adversary

  Yanni Georghiades, Rajesh Mishra, Karl Kreder, Sriram Vishwanath

• Divide-and-Conquer Attack: Harnessing the Power of LLM to Bypass the Censorship of Text-to-Image Generation Model

  Yimo Deng, Huangxun Chen

• Safety Alignment in NLP Tasks: Weakly Aligned Summarization as an In-Context Attack

  Yu Fu, Yufei Li, Wen Xiao, Cong Liu, Yue Dong

• Adversarial Semi-Supervised Domain Adaptation for Semantic Segmentation: A New Role for Labeled Target Samples

  Marwa Kechaou, Mokhtar Z. Alaya, Romain Hérault, Gilles Gasso

• Dynamic Adversarial Attacks on Autonomous Driving Systems

  Amirhosein Chahe, Chenan Wang, Abhishek Jeyapratap, Kaidi Xu, Lifeng Zhou

• AI Control: Improving Safety Despite Intentional Subversion

  Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan, Fabien Roger

• Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning Against Attribute Inference Attacks

  Caridad Arroyo Arevalo, Sayedeh Leila Noorbakhsh, Yun Dong, Yuan Hong, Binghui Wang

2023-12-11

• Towards Transferable Adversarial Attacks with Centralized Perturbation

  Shangbo Wu, Yu-an Tan, Yajie Wang, Ruinan Ma, Wencong Ma, Yuanzhang Li

• MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks

  Yuyang Zhou, Guang Cheng, Zongyao Chen, Shui Yu

• Sparse but Strong: Crafting Adversarially Robust Graph Lottery Tickets

  Subhajit Dutta Chowdhury, Zhiyu Ni, Qingyuan Peng, Souvik Kundu, Pierluigi Nuzzo

• Reward Certification for Policy Smoothed Reinforcement Learning

  Ronghui Mu, Leandro Soriano Marcolino, Tianle Zhang, Yanghao Zhang, Xiaowei Huang, Wenjie Ruan

• Activation Gradient based Poisoned Sample Detection Against Backdoor Attacks

  Danni Yuan, Shaokui Wei, Mingda Zhang, Li Liu, Baoyuan Wu

• Poisoned ChatGPT Finds Work for Idle Hands: Exploring Developers' Coding Practices with Insecure Suggestions from Poisoned AI Models

  Sanghak Oh, Kiho Lee, Seonhye Park, Doowon Kim, Hyoungshick Kim

• Promoting Counterfactual Robustness through Diversity

  Francesco Leofante, Nico Potyka

• Robust Graph Neural Network based on Graph Denoising

  Victor M. Tenorio, Samuel Rey, Antonio G. Marques

• Privacy Preserving Multi-Agent Reinforcement Learning in Supply Chains

  Ananta Mukherjee, Peeyush Kumar, Boling Yang, Nishanth Chandran, Divya Gupta

• Exploring the Limits of ChatGPT in Software Security Applications

  Fangzhou Wu, Qingzhao Zhang, Ati Priya Bajaj, Tiffany Bao, Ning Zhang, Ruoyu "Fish" Wang, Chaowei Xiao

• Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning

  Jianwei Li, Sheng Liu, Qi Lei

• MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks

  Yuyang Zhou, Guang Cheng, Zongyao Chen, Shui Yu

• GTA: Gated Toxicity Avoidance for LM Performance Preservation

  Heegyu Kim, Hyunsouk Cho

• Initialization Matters for Adversarial Transfer Learning

  Andong Hua, Jindong Gu, Zhiyu Xue, Nicholas Carlini, Eric Wong, Yao Qin

• Adversarial Camera Patch: An Effective and Robust Physical-World Attack on Object Detectors

  Kalibinuer Tiliwalidi

• CAD: Photorealistic 3D Generation via Adversarial Distillation

  Ziyu Wan, Despoina Paschalidou, Ian Huang, Hongyu Liu, Bokui Shen, Xiaoyu Xiang, Jing Liao, Leonidas Guibas

• Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation

  Shiji Zhao, Xizhe Wang, Xingxing Wei

• Model Extraction Attacks Revisited

  Jiacheng Liang, Ren Pang, Changjiang Li, Ting Wang

• Poisoning $\times$ Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks

  Ege Erdogan, Simon Geisler, Stephan Günnemann

• A Practical Survey on Emerging Threats from AI-driven Voice Attacks: How Vulnerable are Commercial Voice Control Systems?

  Yuanda Wang, Qiben Yan, Nikolay Ivanov, Xun Chen

• DiffAIL: Diffusion Adversarial Imitation Learning

  Bingzheng Wang, Yan Zhang, Teng Pang, Guoqiang Wu, Yilong Yin

• Security and Reliability Evaluation of Countermeasures implemented using High-Level Synthesis

  Amalia Artemis Koufopoulou, Kalliopi Xevgeni, Athanasios Papadimitriou, Mihalis Psarakis, David Hely

2023-12-10

• zkFDL: An efficient and privacy-preserving decentralized federated learning with zero knowledge proof

  Mojtaba Ahmadi, Reza Nourmohammadi

• Towards Sample-specific Backdoor Attack with Clean Labels via Attribute Trigger

  Yiming Li, Mingyan Zhu, Junfeng Guo, Tao Wei, Shu-Tao Xia, Zhan Qin

• DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

  Fangzhou Wu, Xiaogeng Liu, Chaowei Xiao

• Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks

  Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Ling Cai, Nathalie Baracaldo

• BELT: Old-School Backdoor Attacks can Evade the State-of-the-Art Defense with Backdoor Exclusivity Lifting

  Huming Qiu, Junjie Sun, Mi Zhang, Xudong Pan, Min Yang

• SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation

  Bangyan He, Xiaojun Jia, Siyuan Liang, Tianrui Lou, Yang Liu, Xiaochun Cao

• MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness

  Xiaoyun Xu, Shujian Yu, Jingzheng Wu, Stjepan Picek

• On the Inadequacy of Similarity-based Privacy Metrics: Reconstruction Attacks against "Truly Anonymous Synthetic Data''

  Georgi Ganev, Emiliano De Cristofaro

• MimicDiffusion: Purifying Adversarial Perturbation via Mimicking Clean Diffusion Model

  Kaiyu Song, Hanjiang Lai

• Annotation-Free Group Robustness via Loss-Based Resampling

  Mahdi Ghaznavi, Hesam Asadollahzadeh, HamidReza Yaghoubi Araghi, Fahimeh Hosseini Noohdani, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah

• Diffence: Fencing Membership Privacy With Diffusion Models

  Yuefeng Peng, Ali Naseh, Amir Houmansadr

• HC-Ref: Hierarchical Constrained Refinement for Robust Adversarial Training of GNNs

  Xiaobing Pei, Haoran Yang, Gang Shen

• FedBayes: A Zero-Trust Federated Learning Aggregation to Defend Against Adversarial Attacks

  Marc Vucovich, Devin Quinn, Kevin Choi, Christopher Redino, Abdul Rahman, Edward Bowen

• TrustFed: A Reliable Federated Learning Framework with Malicious-Attack Resistance

  Hangn Su, Jianhong Zhou, Xianhua Niu, Gang Feng

• Topology-Based Reconstruction Prevention for Decentralised Learning

  Florine W. Dekker, Zekeriya Erkin, Mauro Conti

2023-12-09

• Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?

  Kevin Liu, Stephen Casper, Dylan Hadfield-Menell, Jacob Andreas

• On the Learnability of Watermarks for Language Models

  Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto

• Defense against ML-based Power Side-channel Attacks on DNN Accelerators with Adversarial Attacks

  Xiaobei Yan, Chip Hong Chang, Tianwei Zhang

• GaitGuard: Towards Private Gait in Mixed Reality

  Diana Romero, Ruchi Jagdish Patel, Athina Markopolou, Salma Elmalaki

2023-12-08

• An Evaluation of State-of-the-Art Large Language Models for Sarcasm Detection

  Juliann Zhou

• Negotiating with LLMS: Prompt Hacks, Skill Gaps, and Reasoning Deficits

  Johannes Schneider, Steffi Haag, Leona Chandra Kruse

• DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

  Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li, Zhangyang Wang

• Making Translators Privacy-aware on the User's Side

  Ryoma Sato

• Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection

  Jongmin Yu, Hyeontaek Oh, Jinhong Yang

• RoAST: Robustifying Language Models via Adversarial Perturbation with Selective Training

  Jaehyung Kim, Yuning Mao, Rui Hou, Hanchao Yu, Davis Liang, Pascale Fung, Qifan Wang, Fuli Feng, Lifu Huang, Madian Khabsa

• The Potential of Vision-Language Models for Content Moderation of Children's Videos

  Syed Hammad Ahmed, Shengnan Hu, Gita Sukthankar

• On the Impact of Multi-dimensional Local Differential Privacy on Fairness

  karima Makhlouf, Heber H. Arcolezi, Sami Zhioua, Ghassen Ben Brahim, Catuscia Palamidessi

• FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning

  Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger, Alexandra Dmitrienko, Ahmad-Reza Sadeghi

• SoK: Unintended Interactions among Machine Learning Defenses and Risks

  Vasisht Duddu, Sebastian Szyller, N. Asokan

2023-12-07

• GaitGuard: Towards Private Gait in Mixed Reality

  Diana Romero, Ruchi Jagdish Patel, Athina Markopolou, Salma Elmalaki

• Exploring the Robustness of Model-Graded Evaluations and Automated Interpretability

  Simon Lermen, Ondřej Kvapil

• On The Fairness Impacts of Hardware Selection in Machine Learning

  Sree Harsha Nelaturu, Nishaanth Kanna Ravichandran, Cuong Tran, Sara Hooker, Ferdinando Fioretto

• Detecting and Restoring Non-Standard Hands in Stable Diffusion Generated Images

  Yiqun Zhang, Zhenyue Qin, Yang Liu, Dylan Campbell

• Adversarial Learning for Feature Shift Detection and Correction

  Miriam Barrabes, Daniel Mas Montserrat, Margarita Geleta, Xavier Giro-i-Nieto, Alexander G. Ioannidis

• OT-Attack: Enhancing Adversarial Transferability of Vision-Language Models via Optimal Transport Optimization

  Dongchen Han, Xiaojun Jia, Yang Bai, Jindong Gu, Yang Liu, Xiaochun Cao

• FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning

  Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger, Alexandra Dmitrienko, Ahmad-Reza Sadeghi

2023-12-06

• Defense against ML-based Power Side-channel Attacks on DNN Accelerators with Adversarial Attacks

  Xiaobei Yan, Chip Hong Chang, Tianwei Zhang

• Defense Against Adversarial Attacks using Convolutional Auto-Encoders

  Shreyasi Mandal

• Node-aware Bi-smoothing: Certified Robustness against Graph Injection Attacks

  Yuni Lai, Yulin Zhu, Bailin Pan, Kai Zhou

• Privacy-preserving quantum federated learning via gradient hiding

  Changhao Li, Niraj Kumar, Zhixin Song, Shouvanik Chakrabarti, Marco Pistoia

• RoAST: Robustifying Language Models via Adversarial Perturbation with Selective Training

  Jaehyung Kim, Yuning Mao, Rui Hou, Hanchao Yu, Davis Liang, Pascale Fung, Qifan Wang, Fuli Feng, Lifu Huang, Madian Khabsa

• Analyzing the Inherent Response Tendency of LLMs: Real-World Instructions-Driven Jailbreak

  Yanrui Du, Sendong Zhao, Ming Ma, Yuhan Chen, Bing Qin

• Detecting Voice Cloning Attacks via Timbre Watermarking

  Chang Liu, Jie Zhang, Tianwei Zhang, Xi Yang, Weiming Zhang, Nenghai Yu

• Identity-Obscured Neural Radiance Fields: Privacy-Preserving 3D Facial Reconstruction

  Jiayi Kong, Baixin Xu, Xurui Song, Chen Qian, Jun Luo, Ying He

• Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection

  Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh

• Synthesizing Physical Backdoor Datasets: An Automated Framework Leveraging Deep Generative Models

  Sze Jue Yang, Chinh D. La, Quang H. Nguyen, Eugene Bagdasaryan, Kok-Seng Wong, Anh Tuan Tran, Chee Seng Chan, Khoa D. Doan

• MICRO: Model-Based Offline Reinforcement Learning with a Conservative Bellman Operator

  Xiao-Yin Liu, Xiao-Hu Zhou, Guo-Tao Li, Hao Li, Mei-Jiang Gui, Tian-Yu Xiang, De-Xing Huang, Zeng-Guang Hou

2023-12-05

• Generating Visually Realistic Adversarial Patch

  Xiaosen Wang, Kunyu Wang

• ScAR: Scaling Adversarial Robustness for LiDAR Object Detection

  Xiaohu Lu, Hayder Radha

• A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection System

  Xinwei Yuan, Shu Han, Wei Huang, Hongliang Ye, Xianglong Kong, Fan Zhang

• Realistic Scatterer Based Adversarial Attacks on SAR Image Classifiers

  Tian Ye, Rajgopal Kannan, Viktor Prasanna, Carl Busart, Lance Kaplan

• Class Incremental Learning for Adversarial Robustness

  Seungju Cho, Hongshin Lee, Changick Kim

• (Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More

  Jan Schuchardt, Yan Scholten, Stephan Günnemann

• On the Robustness of Large Multimodal Models Against Image Adversarial Attacks

  Xuanimng Cui, Alejandro Aparcedo, Young Kyun Jang, Ser-Nam Lim

• Scaling Laws for Adversarial Attacks on Language Model Activations

  Stanislav Fort

• Indirect Gradient Matching for Adversarial Robust Distillation

  Hongsin Lee, Seungju Cho, Changick Kim

• Robust Backdoor Detection for Deep Learning via Topological Evolution Dynamics

  Xiaoxing Mo, Yechao Zhang, Leo Yu Zhang, Wei Luo, Nan Sun, Shengshan Hu, Shang Gao, Yang Xiang

• Prompt Optimization via Adversarial In-Context Learning

  Xuan Long Do, Yiran Zhao, Hannah Brown, Yuxi Xie, James Xu Zhao, Nancy F. Chen, Kenji Kawaguchi, Michael Qizhe Xie, Junxian He

• Privacy-Preserving Task-Oriented Semantic Communications Against Model Inversion Attacks

  Yanhu Wang, Shuaishuai Guo, Yiqin Deng, Haixia Zhang, Yuguang Fang

• Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning

  Zhuo Huang, Chang Liu, Yinpeng Dong, Hang Su, Shibao Zheng, Tongliang Liu

2023-12-04

• Adversarial Medical Image with Hierarchical Feature Hiding

  Qingsong Yao, Zecheng He, Yuexiang Li, Yi Lin, Kai Ma, Yefeng Zheng, S. Kevin Zhou

• InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language Models

  Xunguang Wang, Zhenlan Ji, Pingchuan Ma, Zongjie Li, Shuai Wang

• Singular Regularization with Information Bottleneck Improves Model's Adversarial Robustness

  Guanlin Li, Naishan Zheng, Man Zhou, Jie Zhang, Tianwei Zhang

• Two-stage optimized unified adversarial patch for attacking visible-infrared cross-modal detectors in the physical world

  Chengyin Hu, Weiwen Shi

• Auto DP-SGD: Dual Improvements of Privacy and Accuracy via Automatic Clipping Threshold and Noise Multiplier Estimation

  Sai Venkatesh Chilukoti, Md Imran Hossen, Liqun Shan, Vijay Srinivas Tida, Xiai Hei

• Rejuvenating image-GPT as Strong Visual Representation Learners

  Sucheng Ren, Zeyu Wang, Hongru Zhu, Junfei Xiao, Alan Yuille, Cihang Xie

2023-12-03

• QuantAttack: Exploiting Dynamic Quantization to Attack Vision Transformers

  Amit Baras, Alon Zolfi, Yuval Elovici, Asaf Shabtai

• OCGEC: One-class Graph Embedding Classification for DNN Backdoor Detection

  Haoyu Jiang, Haiyang Yu, Nan Li, Ping Yi

• Evaluating the Security of Satellite Systems

  Roy Peled, Eran Aizikovich, Edan Habler, Yuval Elovici, Asaf Shabtai

• Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving

  Bo Yang, Xiaoyu Ji, Xiaoyu Ji, Xiaoyu Ji, Xiaoyu Ji

2023-12-02

• TranSegPGD: Improving Transferability of Adversarial Examples on Semantic Segmentation

  Xiaojun Jia, Jindong Gu, Yihao Huang, Simeng Qin, Qing Guo, Yang Liu, Xiaochun Cao

• Rethinking PGD Attack: Is Sign Function Necessary? (98%

  Junjie Yang, Tianlong Chen, Xuxi Chen, Zhangyang Wang, Yingbin Liang

• PROFL: A Privacy-Preserving Federated Learning Method with Stringent Defense Against Poisoning Attacks

  Yisheng Zhong, Li-Ping Wang

• Mendata: A Framework to Purify Manipulated Training Data

  Zonghao Huang, Neil Gong, Michael K. Reiter

2023-12-01

• PyraTrans: Learning Attention-Enriched Multi-Scale Pyramid Network from Pre-Trained Transformers for Effective Malicious URL Detection

  Ruitong Liu, Yanbin Wang, Zhenhao Guo, Haitao Xu, Zhan Qin, Wenrui Ma, Fan Zhang

• Survey of Security Issues in Memristor-based Machine Learning Accelerators for RF Analysis

  William Lillis, Max Cohen Hoffing, Wayne Burleson

• Deep Generative Attacks and Countermeasures for Data-Driven Offline Signature Verification

  An Ngo, MinhPhuong Cao, Rajesh Kumar

• Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training

  Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang

2023-11-30

• Improving Faithfulness for Vision Transformers

  Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang

• TrustMark: Universal Watermarking for Arbitrary Resolution Images

  Tu Bui, Shruti Agarwal, John Collomosse

• Unnatural Error Correction: GPT-4 Can Almost Perfectly Handle Unnatural Scrambled Text

  Qi Cao, Takeshi Kojima, Yutaka Matsuo, Yusuke Iwasawa

• ROBBIE: Robust Bias Evaluation of Large Generative Language Models

  David Esiobu, Xiaoqing Tan, Saghar Hosseini, Megan Ung, Yuchen Zhang, Jude Fernandes, Jane Dwivedi-Yu, Eleonora Presani, Adina Williams, Eric Michael Smith

• What Do Llamas Really Think? Revealing Preference Biases in Language Model Representations

  Raphael Tang, Xinyu Zhang, Jimmy Lin, Ferhan Ture

• Improving Adversarial Transferability via Model Alignment

  Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip Torr, Jindong Gu

• Poisoning Attacks Against Contrastive Recommender Systems

  Zongwei Wang, Junliang Yu, Min Gao, Hongzhi Yin, Bin Cui, Shazia Sadiq

2023-11-29

• Improving the Robustness of Transformer-based Large Language Models with Dynamic Attention

Lujia Shen, Yuwen Pu, Shouling Ji, Changjiang Li, Xuhong Zhang, Chunpeng Ge, Ting Wang

• Group-wise Sparse and Explainable Adversarial Attacks

Shpresim Sadiku, Moritz Wagner, Sebastian Pokutta

• Quantum Neural Networks under Depolarization Noise: Exploring White-Box Attacks and Defenses

David Winderl, Nicola Franco, Jeanette Miriam Lorenz

• On the Adversarial Robustness of Graph Contrastive Learning Methods

Filippo Guerranti, Zinuo Yi, Anna Starovoit, Rafiq Kamel, Simon Geisler, Stephan Günnemann

• Adversarial Robust Memory-Based Continual Learner

Xiaoyue Mi, Fan Tang, Zonghan Yang, Danding Wang, Juan Cao, Peng Li, Yang Liu

• TARGET: Template-Transferable Backdoor Attack Against Prompt-based NLP Models via GPT4

Zihao Tan, Qingliang Chen, Yongjian Huang, Chen Liang

• Topology-Preserving Adversarial Training

Xiaoyue Mi, Fan Tang, Yepeng Weng, Danding Wang, Juan Cao, Sheng Tang, Peng Li, Yang Liu

• Query-Relevant Images Jailbreak Large Multi-Modal Models

Xin Liu, Yichen Zhu, Yunshi Lan, Chao Yang, Yu Qiao

• Analyzing and Explaining Image Classifiers via Diffusion Guidance

Maximilian Augustin, Yannic Neuhaus, Matthias Hein

• SenTest: Evaluating Robustness of Sentence Encoders

Tanmay Chavan, Shantanu Patankar, Aditya Kane, Omkar Gokhale, Geetanjali Kale, Raviraj Joshi

• CLIPC8: Face liveness detection algorithm based on image-text pairs and contrastive learning

Xu Liu, Shu Zhou, Yurong Song, Wenzhe Luo, Xin Zhang

2023-11-28

• Unveiling the Implicit Toxicity in Large Language Models

Jiaxin Wen, Pei Ke, Hao Sun, Zhexin Zhang, Chengfei Li, Jinfeng Bai, Minlie Huang

• Vulnerability Analysis of Transformer-based Optical Character Recognition to Adversarial Attacks

Lucas Beerens, Desmond J. Higham

• NeRFTAP: Enhancing Transferability of Adversarial Patches on Face Recognition using Neural Radiance Fields

Xiaoliang Liu, Furao Shen, Feng Han, Jian Zhao, Changhai Nie

• Efficient Key-Based Adversarial Defense for ImageNet by Using Pre-trained Model

AprilPyone MaungMaung, Isao Echizen, Hitoshi Kiya

• RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches on Face Recognition

Xiaoliang Liu, Furao Shen, Jian Zhao, Changhai Nie

• 1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness

Bernd Prach, Fabio Brau, Giorgio Buttazzo, Christoph H. Lampert

• Scalable Extraction of Training Data from (Production) Language Models

Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, Katherine Lee

• Cooperative Abnormal Node Detection with Adversary Resistance: A Probabilistic Approach

Yingying Huangfu, Tian Bai

• Shadows Don't Lie and Lines Can't Bend! Generative Models don't know Projective Geometry

Ayush Sarkar, Hanlin Mai, Amitabh Mahapatra, Svetlana Lazebnik, D. A. Forsyth, Anand Bhattad

• On robust overfitting: adversarial training induced distribution matters

Runzhi Tian, Yongyi Mao

• Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations

Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin

2023-11-27

• Rethinking Mixup for Improving the Adversarial Transferability

Xiaosen Wang, Zeyuan Yin

• Microarchitectural Security of AWS Firecracker VMM for Serverless Cloud Platforms

  Zane Worcester Polytechnic Institute Weissman, Thore University of Lübeck Tiemann, Thomas University of Lübeck Eisenbarth, Berk Worcester Polytechnic Institute Sunar

• Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale

  Soyed Tuhin Ahmed, Kamal Danouchi, Michael Hefenbrock, Guillaume Prenat, Lorena Anghel, Mehdi B. Tahoori

• Instruct2Attack: Language-Guided Semantic Adversarial Attacks

  Jiang Liu, Chen Wei, Yuxiang Guo, Heng Yu, Alan Yuille, Soheil Feizi, Chun Pong Lau, Rama Chellappa

• A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective

  Xianghua Xie, Chen Hu, Hanchi Ren, Jingjing Deng

• Distributed Attacks over Federated Reinforcement Learning-enabled Cell Sleep Control

  Han Zhang, Hao Zhou, Medhat Elsayed, Majid Bavand, Raimundas Gaigalas, Yigit Ozcan, Melike Erol-Kantarci

• How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

  Haoqin Tu, Chenhang Cui, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, Cihang Xie

• Trainwreck: A damaging adversarial attack on image classifiers

  Jan Zahálka

• Adversaral Doodles: Interpretable and Human-drawable Attacks Provide Describable Insights

  Ryoya Nara, Yusuke Matsui

• Automated discovery of trade-off between utility, privacy and fairness in machine learning models

  Bogdan Ficiu, Neil D. Lawrence, Andrei Paleyes

• Attend Who is Weak: Enhancing Graph Condensation via Cross-Free Adversarial Training

  Xinglin Li, Kun Wang, Hanhui Deng, Yuxuan Liang, Di Wu

• Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective

  Lukas Wutschitz, Boris Köpf, Andrew Paverd, Saravan Rajmohan, Ahmed Salem, Shruti Tople, Santiago Zanella-Béguelin, Menglin Xia, Victor Rühle

2023-11-26

• Confidence Is All You Need for MI Attacks

  Abhishek Sinha, Himanshi Tibrewal, Mansi Gupta, Nikhar Waghela, Shivank Garg

• Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off

  Yatong Bai, Brendon G. Anderson, Somayeh Sojoudi

• Adversarial Purification of Information Masking

  Sitong Liu, Zhichao Lian, Shuangquan Zhang, Liang Xiao

• Having Second Thoughts? Let's hear it

  Jung H. Lee, Sujith Vijayan

2023-11-25

• Effective Backdoor Mitigation Depends on the Pre-training Objective

  Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P Dickerson, Jeff Bilmes

• Robust Graph Neural Networks via Unbiased Aggregation

  Ruiqi Feng, Zhichao Hou, Tyler Derr, Xiaorui Liu

• Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off

  Yatong Bai, Brendon G. Anderson, Somayeh Sojoudi

• Robust Graph Neural Networks via Unbiased Aggregation

  Ruiqi Feng, Zhichao Hou, Tyler Derr, Xiaorui Liu

• Effective Backdoor Mitigation Depends on the Pre-training Objective

  Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P Dickerson, Jeff Bilmes

2023-11-24

• Universal Jailbreak Backdoors from Poisoned Human Feedback

  Javier Rando, Florian Tramèr

• How to ensure a safe control strategy? Towards a SRL for urban transit autonomous operation

  Zicong Zhao

• Potential Societal Biases of ChatGPT in Higher Education: A Scoping Review

  Ming Li, Ariunaa Enkhtur, Beverley Anne Yamamoto, Fei Cheng

• AI-based Attack Graph Generation

  Sangbeom Park, Jaesung Lee, Jeongdo Yoo, Min Geun Song, Hyosun Lee, Jaewoong Choi, Chaeyeon Sagong, Huy Kang Kim

• Segment (Almost) Nothing: Prompt-Agnostic Adversarial Attacks on Segmentation Models

  Francesco Croce, Matthias Hein

• Universal Jailbreak Backdoors from Poisoned Human Feedback

  Javier Rando, Florian Tramèr

2023-11-23

• Exploring Methods for Cross-lingual Text Style Transfer: The Case of Text Detoxification

  Daryna Dementieva, Daniil Moskovskiy, David Dale, Alexander Panchenko

• Efficient Trigger Word Insertion

  Yueqi Zeng, Ziqiang Li, Pengfei Xia, Lei Liu, Bin Li

• ACT: Adversarial Consistency Models

  Fei Kong, Jinhao Duan, Lichao Sun, Hao Cheng, Renjing Xu, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu

• Robust and Interpretable COVID-19 Diagnosis on Chest X-ray Images using Adversarial Training

  Karina Yang, Alexis Bennett, Dominique Duncan

• When Side-Channel Attacks Break the Black-Box Property of Embedded Artificial Intelligence

  Benoit Coqueret, Mathieu Carbone, Olivier Sentieys, Gabriel Zaid

• Adversarial defense based on distribution transfer

  Jiahao Chen, Diqun Yan, Li Dong

• Robust and Interpretable COVID-19 Diagnosis on Chest X-ray Images using Adversarial Training

  Karina Yang, Alexis Bennett, Dominique Duncan

2023-11-22

• Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models

  Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake C. Snell, Toniann Pitassi, Richard Zemel

• A Theoretical Insight into Attack and Defense of Gradient Leakage in Transformer

  Chenyang Li, Zhao Song, Weixin Wang, Chiwun Yang

• OASIS: Offsetting Active Reconstruction Attacks in Federated Learning

  Tre' R. Jeter, Truc Nguyen, Raed Alharbi, My T. Thai

• RAEDiff: Denoising Diffusion Probabilistic Models Based Reversible Adversarial Examples Self-Generation and Self-Recovery

  Fan Xing, Xiaoyi Zhou, Xuefeng Fan, Zhuo Tian, Yan Zhao

• A Survey of Adversarial CAPTCHAs on its History, Classification and Generation

  Zisheng Xu, Qiao Yan, F. Richard Yu, Victor C. M. Leung

• Panda or not Panda? Understanding Adversarial Attacks with Interactive Visualization

  Yuzhe You, Jarvis Tse, Jian Zhao

• Security and Privacy Challenges in Deep Learning Models

  Gopichandh Golla

• A Somewhat Robust Image Watermark against Diffusion-based Editing Models

  Mingtian Tan, Tianhao Wang, Somesh Jha

• Adversarial sample generation and training using geometric masks for accurate and resilient license plate character recognition

  Bishal Shrestha, Griwan Khakurel, Kritika Simkhada, Badri Adhikari

• Attention Deficit is Ordered! Fooling Deformable Vision Transformers with Collaborative Adversarial Patches

  Quazi Mishkatul Alam, Bilel Tarchoun, Ihsen Alouani, Nael Abu-Ghazaleh

• SD-NAE: Generating Natural Adversarial Examples with Stable Diffusion

  Yueqian Lin, Jingyang Zhang, Yiran Chen, Hai Li

• Hard Label Black Box Node Injection Attack on Graph Neural Networks

  Yu Zhou, Zihao Dong, Guofeng Zhang, Jingchen Tang

• Transfer Attacks and Defenses for Large Language Models on Coding Tasks

  Chi Zhang, Zifan Wang, Ravi Mangal, Matt Fredrikson, Limin Jia, Corina Pasareanu

2023-11-21

• Boost Adversarial Transferability by Uniform Scale and Mix Mask Method

  Tao Wang, Zijian Ying, Qianmu Li, zhichao Lian

• BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive Learning

  Siyuan Liang, Mingli Zhu, Aishan Liu, Baoyuan Wu, Xiaochun Cao, Ee-Chien Chang

• Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack Detection

  Renu Sharma, Redwan Sony, Arun Ross

• Iris Presentation Attack: Assessing the Impact of Combining Vanadium Dioxide Films with Artificial Eyes

  Darshika Jauhari, Renu Sharma, Cunjian Chen, Nelson Sepulveda, Arun Ross

• ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches

  Nandish Chattopadhyay, Amira Guesmi, Muhammad Abdullah Hanif, Bassem Ouni, Muhammad Shafique

• Attacking Motion Planners Using Adversarial Perception Errors

  Jonathan Sadeghi, Nicholas A. Lord, John Redford, Romain Mueller

• Masked Autoencoders Are Robust Neural Architecture Search Learners

  Yiming Hu, Xiangxiang Chu, Bo Zhang

• Adversarial Reweighting Guided by Wasserstein Distance for Bias Mitigation

  Xuan Zhao, Simone Fabbrizzi, Paula Reyero Lobo, Siamak Ghodsi, Klaus Broelemann, Steffen Staab, Gjergji Kasneci

• Attacks of fairness in Federated Learning

  Joseph Rance, Filip Svoboda

• DefensiveDR: Defending against Adversarial Patches using Dimensionality Reduction

  Nandish Chattopadhyay, Amira Guesmi, Muhammad Abdullah Hanif, Bassem Ouni, Muhammad Shafique

2023-11-20

• Safety-aware Causal Representation for Trustworthy Reinforcement Learning in Autonomous Driving

  Haohong Lin, Wenhao Ding, Zuxin Liu, Yaru Niu, Jiacheng Zhu, Yuming Niu, Ding Zhao

• Assessing Prompt Injection Risks in 200+ Custom GPTs

  Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, Xinyu Xin

• Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems

  Guangjing Wang, Ce Zhou, Yuanda Wang, Bocheng Chen, Hanqing Guo, Qiben Yan

• Generating Valid and Natural Adversarial Examples with Large Language Models

  Zimu Wang, Wei Wang, Qi Chen, Qiufeng Wang, Anh Nguyen

• AdvGen: Physical Adversarial Attack on Face Presentation Attack Detection Systems

  Sai Amrit Patnaik, Shivali Chansoriya, Anil K. Jain, Anoop M. Namboodiri

• Understanding Variation in Subpopulation Susceptibility to Poisoning Attacks

  Evan Rose, Fnu Suya, David Evans

• Training robust and generalizable quantum models

  Julian Berberich, Daniel Fink, Daniel Pranjić, Christian Tutschku, Christian Holm

• BrainWash: A Poisoning Attack to Forget in Continual Learning

  Ali Abbasi, Parsa Nooralinejad, Hamed Pirsiavash, Soheil Kolouri

2023-11-19

• Robust Network Slicing: Multi-Agent Policies, Adversarial Attacks, and Defensive Strategies

  Feng Wang, M. Cenk Gursoy, Senem Velipasalar

• Adversarial Prompt Tuning for Vision-Language Models

  Jiaming Zhang, Xingjun Ma, Xin Wang, Lingyu Qiu, Jiaqi Wang, Yu-Gang Jiang, Jitao Sang

• TextGuard: Provable Defense against Backdoor Attacks on Text Classification

  Hengzhi Pei, Jinyuan Jia, Wenbo Guo, Bo Li, Dawn Song

2023-11-18

• Improving Adversarial Transferability by Stable Diffusion

  Jiayang Liu, Siyu Zhu, Siyuan Liang, Jie Zhang, Han Fang, Weiming Zhang, Ee-Chien Chang

• Attention-Based Real-Time Defenses for Physical Adversarial Attacks in Vision Applications

  Giulio Rossolini, Alessandro Biondi, Giorgio Buttazzo

• PACOL: Poisoning Attacks Against Continual Learners

  Huayu Li, Gregory Ditzler

• Robust Network Slicing: Multi-Agent Policies, Adversarial Attacks, and Defensive Strategies

  Feng Wang, M. Cenk Gursoy, Senem Velipasalar

2023-11-17

• Robustness Enhancement in Neural Networks with Alpha-Stable Training Noise

  Xueqiong Yuan, Jipeng Li, Ercan Engin Kuruoğlu

• Breaking Temporal Consistency: Generating Video Universal Adversarial Perturbations Using Image Models

  Hee-Seon Kim, Minji Son, Minbeom Kim, Myung-Joon Kwon, Changick Kim

• PACOL: Poisoning Attacks Against Continual Learners

  Huayu Li, Gregory Ditzler

• Two-Factor Authentication Approach Based on Behavior Patterns for Defeating Puppet Attacks

  Wenhao Wang, Guyue Li, Zhiming Chu, Haobo Li, Daniele Faccio

2023-11-16

• Breaking Boundaries: Balancing Performance and Robustness in Deep Wireless Traffic Forecasting

  Ilbert Romain, V. Hoang Thai, Zhang Zonghua, Palpanas Themis

• Hijacking Large Language Models via Adversarial In-Context Learning

  Yao Qiang, Xiangyu Zhou, Dongxiao Zhu

• Cognitive Overload: Jailbreaking Large Language Models with Overloaded Logical Thinking

  Nan Xu, Fei Wang, Ben Zhou, Bang Zheng Li, Chaowei Xiao, Muhao Chen

• Test-time Backdoor Mitigation for Black-Box Large Language Models with Defensive Demonstrations

  Wenjie Mo, Jiashu Xu, Qin Liu, Jiongxiao Wang, Jun Yan, Chaowei Xiao, Muhao Chen

• On the Exploitability of Reinforcement Learning with Human Feedback for Large Language Models

  Jiongxiao Wang, Junlin Wu, Muhao Chen, Yevgeniy Vorobeychik, Chaowei Xiao

• Towards more Practical Threat Models in Artificial Intelligence Security

  Kathrin Grosse, Lukas Bieringer, Tarek Richard Besold, Alexandre Alahi

2023-11-15

• Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts

  Yuanwei Wu, Xiang Li, Yixin Liu, Pan Zhou, Lichao Sun

• Backdoor Activation Attack: Attack Large Language Models using Activation Steering for Safety-Alignment

  Haoran Wang, Kai Shu

• Fast Certification of Vision-Language Models Using Incremental Randomized Smoothing

  A K Iowa State University Nirala, A New York University Joshi, C New York University Hegde, S Iowa State University Sarkar

• Adversarially Robust Spiking Neural Networks Through Conversion

  Ozan Özdenizci, Robert Legenstein

• Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

  Zhexin Zhang, Junxiao Yang, Pei Ke, Minlie Huang

• Privacy Threats in Stable Diffusion Models

  Thomas Cilloni, Charles Fleming, Charles Walter

• How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities

  Lingbo Mo, Boshi Wang, Muhao Chen, Huan Sun

• MirrorNet: A TEE-Friendly Framework for Secure On-device DNN Inference

  Ziyu Liu, Yukui Luo, Shijin Duan, Tong Zhou, Xiaolin Xu

• Beyond Detection: Unveiling Fairness Vulnerabilities in Abusive Language Models

  Yueqing Liang, Lu Cheng, Ali Payani, Kai Shu

• JAB: Joint Adversarial Prompting and Belief Augmentation

  Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Jwala Dhamala, Shalini Ghosh, Richard Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta

2023-11-14

• Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning

  Shashank Kotyan, Danilo Vasconcellos Vargas

• Physical Adversarial Examples for Multi-Camera Systems

  Ana Răduţoiu, Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger

• DALA: A Distribution-Aware LoRA-Based Adversarial Attack against Pre-trained Language Models

  Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu

• On The Relationship Between Universal Adversarial Attacks And Sparse Representations

  Dana Weitzner, Raja Giryes

• A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily

  Peng Ding, Jun Kuang, Dan Ma, Xuezhi Cao, Yunsen Xian, Jiajun Chen, Shujian Huang

• Multi-Set Inoculation: Assessing Model Robustness Across Multiple Challenge Sets

  Vatsal Gupta, Pranshu Pandya, Tushar Kataria, Vivek Gupta, Dan Roth

• The Perception-Robustness Tradeoff in Deterministic Image Restoration

  Guy Ohayon, Tomer Michaeli, Michael Elad

2023-11-13

• Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models

  Yuanbin Cheng, Koji Yamashita, Jim Follum, Nanpeng Yu

• Parrot-Trained Adversarial Examples: Pushing the Practicality of Black-Box Audio Attacks against Speaker Recognition Models

  Rui Duan, Zhe Qu, Leah Ding, Yao Liu, Zhuo Lu

• An Extensive Study on Adversarial Attack against Pre-trained Models of Code

  Xiaohu Du, Ming Wen, Zichao Wei, Shangwen Wang, Hai Jin

• Untargeted Black-box Attacks for Social Recommendations

  Wenqi Fan, Shijie Wang, Xiao-yong Wei, Xiaowei Mei, Qing Li

• On the Robustness of Neural Collapse and the Neural Collapse of Robustness

  Jingtong Su, Ya Shi Zhang, Nikolaos Tsilivis, Julia Kempe

• Tabdoor: Backdoor Vulnerabilities in Transformer-based Neural Networks for Tabular Data

  Bart Pleiter, Behrad Tajalli, Stefanos Koffas, Gorka Abad, Jing Xu, Martha Larson, Stjepan Picek

2023-11-12

• Learning Globally Optimized Language Structure via Adversarial Training

  Xuwang Yin

• Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks

  Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb

• Analytical Verification of Deep Neural Network Performance for Time-Synchronized Distribution System State Estimation

    Behrouz Azimian, Shiva Moshtagh, Anamitra Pal, Shanshan Ma
  

• DialMAT: Dialogue-Enabled Transformer with Moment-Based Adversarial Training

  Kanta Kaneda, Ryosuke Korekata, Yuiga Wada, Shunya Nagashima, Motonari Kambara, Yui Iioka, Haruka Matsuo, Yuto Imai, Takayuki Nishimura, Komei Sugiura

2023-11-10

• Robust Adversarial Attacks Detection for Deep Learning based Relative Pose Estimation for Space Rendezvous

  Ziwei Wang, Nabil Aouf, Jose Pizarro, Christophe Honvault

• Summon a Demon and Bind it: A Grounded Theory of LLM Red Teaming in the Wild

  Nanna Inie, Jonathan Stray, Leon Derczynski

• Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction

  Shanghao Shi, Ning Wang, Yang Xiao, Chaoyu Zhang, Yi Shi, Y.Thomas Hou, Wenjing Lou

• Does Differential Privacy Prevent Backdoor Attacks in Practice?

  Fereshteh Razmi, Jian Lou, Li Xiong

• Flatness-aware Adversarial Attack

  Mingyuan Fan, Xiaodan Li, Cen Chen, Yinggui Wang

• Robust Adversarial Attacks Detection for Deep Learning based Relative Pose Estimation for Space Rendezvous.

  Ziwei Wang, Nabil Aouf, Jose Pizarro, Christophe Honvault

• Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches

  Jianan Feng, Jiachun Li, Changqing Miao, Jianjun Huang, Wei You, Wenchang Shi, Bin Liang

• Resilient and constrained consensus against adversarial attacks: A distributed MPC framework

  Henglai Wei, Kunwu Zhang, Hui Zhang, Yang Shi

• CALLOC: Curriculum Adversarial Learning for Secure and Robust Indoor Localization

  Danish Gufran, Sudeep Pasricha

• Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

  Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang

2023-11-09

• Counter-Empirical Attacking based on Adversarial Reinforcement Learning for Time-Relevant Scoring System

  Xiangguo Sun, Hong Cheng, Hang Dong, Bo Qiao, Si Qin, Qingwei Lin

• SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data

  Meiling Fang, Marco Huber, Julian Fierrez, Raghavendra Ramachandra, Naser Damer, Alhasan Alkhaddour, Maksim Kasantcev, Vasiliy Pryadchenko, Ziyuan Yang, Huijie Huangfu, Yingyu Chen, Yi Zhang, Yuchen Pan, Junjun Jiang, Xianming Liu, Xianyun Sun, Caiyong Wang, Xingyu Liu, Zhaohua Chang, Guangzhe Zhao, Juan Tapia, Lazaro Gonzalez-Soler, Carlos Aravena, Daniel Schulz

• Counter-Empirical Attacking based on Adversarial Reinforcement Learning for Time-Relevant Scoring System

  Xiangguo Sun, Hong Cheng, Hang Dong, Bo Qiao, Si Qin, Qingwei Lin

• SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training

  Rui Xu, Wenkang Qin, Peixiang Huang, Haowang, Lin Luo

• Training Robust Deep Physiological Measurement Models with Synthetic Video-based Data

  Yuxuan Ou, Yuzhe Zhang, Yuntang Wang, Shwetak Patel, Daniel McDuf, Xin Liu

• FigStep: Jailbreaking Large Vision-language Models via Typographic Visual Prompts

  Yichen Gong, Delong Ran, Jinyuan Liu, Conglei Wang, Tianshuo Cong, Anyu Wang, Sisi Duan, Xiaoyun Wang

2023-11-8

• Familiarity-Based Open-Set Recognition Under Adversarial Attacks

  Philip Enevoldsen, Christian Gundersen, Nico Lang, Serge Belongie, Christian Igel

• Edge-assisted U-Shaped Split Federated Learning with Privacy-preserving for Internet of Things

  Hengliang Tang, Zihang Zhao, Detian Liu, Yang Cao, Shiqiang Zhang, Siqing You

• DEMASQ: Unmasking the ChatGPT Wordsmith

  Kavita Kumari, Alessandro Pegoraro, Hossein Fereidooni, Ahmad-Reza Sadeghi

• On the steerability of large language models toward data-driven personas

  Junyi Li, Ninareh Mehrabi, Charith Peris, Palash Goyal, Kai-Wei Chang, Aram Galstyan, Richard Zemel, Rahul Gupta

2023-11-7

• FD-MIA: Efficient Attacks on Fairness-enhanced Models

  Huan Tian, Guangsheng Zhang, Bo Liu, Tianqing Zhu, Ming Ding, Wanlei Zhou

• Unveiling Safety Vulnerabilities of Large Language Models

  George Kour, Marcel Zalmanovici, Naama Zwerdling, Esther Goldbraich, Ora Nova Fandina, Ateret Anaby-Tavor, Orna Raz, Eitan Farchi

2023-11-6

• A Preference Learning Approach to Develop Safe and Personalizable Autonomous Vehicles

  Ruya Karagulle, Nikos Arechiga, Andrew Best, Jonathan DeCastro, Necmiye Ozay

• Making Harmful Behaviors Unlearnable for Large Language Models

  Xin Zhou, Yi Lu, Ruotian Ma, Tao Gui, Qi Zhang, Xuanjing Huang

• Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities

  Wenchong He, Zhe Jiang

• On the Intersection of Self-Correction and Trust in Language Models

  Satyapriya Krishna

• Preserving Privacy in GANs Against Membership Inference Attack

  Mohammadhadi Shateri, Francisco Messina, Fabrice Labeau, Pablo Piantanida

• DeepInception: Hypnotize Large Language Model to Be Jailbreaker

  Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, Bo Han

2023-11-5

• Pilot-Based Key Distribution and Encryption for Secure Coherent Passive Optical Networks

  Haide Wang, Ji Zhou, Qingxin Lu, Jianrui Zeng, Yongqing Liao, Weiping Liu, Changyuan Yu, Zhaohui Li

• ELEGANT: Certified Defense on the Fairness of Graph Neural Networks

  Yushun Dong; Binchi Zhang; Hanghang Tong; Jundong Li

2023-11-4

• From Trojan Horses to Castle Walls: Unveiling Bilateral Backdoor Effects in Diffusion Models

  Zhuoshi Pan, Yuguang Yao, Gaowen Liu, Bingquan Shen, H. Vicky Zhao, Ramana Rao Kompella, Sijia Liu

2023-11-3

• Can AI Mitigate Human Perceptual Biases? A Pilot Study

  Ross Geuy, Nate Rising, Tiancheng Shi, Meng Ling, Jian Chen

• SCPO: Safe Reinforcement Learning with Safety Critic Policy Optimization

  Jaafar Mhamed, Shangding Gu

• Robust Identity Perceptual Watermark Against Deepfake Face Swapping

  Tianyi Wang, Mengxiao Huang, Harry Cheng, Bin Ma, Yinglong Wang

• A Call to Arms: AI Should be Critical for Social Media Analysis of Conflict Zones

  Afia Abedin, Abdul Bais, Cody Buntain, Laura Courchesne, Brian McQuinn, Matthew E. Taylor, Muhib Ullah

• Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game

  Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell

• MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training

  Jiacheng Li, Ninghui Li, Bruno Ribeiro

• Reputation Systems for Supply Chains: The Challenge of Achieving Privacy Preservation

  Lennart Bader, Jan Pennekamp, Emildeon Thevaraj, Maria Spiß, Salil S. Kanhere, Klaus Wehrle

2023-11-2

• Optimal Cost Constrained Adversarial Attacks For Multiple Agent Systems

  Ziqing Lu, Guanlin Liu, Lifeng Cai, Weiyu Xu

• SCPO: Safe Reinforcement Learning with Safety Critic Policy Optimization

  Jaafar Mhamed, Shangding Gu

• Generate and Pray: Using SALLMS to Evaluate the Security of LLM Generated Code

  Mohammed Latif Siddiq, Joanna C. S. Santos

• Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent

  Lorenz Kummer, Samir Moustafa, Nils N. Kriege, Wilfried N. Gansterer

• Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly

  Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen

• Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game

  Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell

• In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer

  Yuzhou Cao, Hussein Mozannar, Lei Feng, Hongxin Wei, Bo An

• MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training

  Jiacheng Li, Ninghui Li, Bruno Ribeiro

2023-11-1

• FAIRLABEL: Correcting Bias in Labels

  Srinivasan H Sengamedu, Hien Pham

• Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation

  Xiangjue Dong, Yibo Wang, Philip S. Yu, James Caverlee

• Robustness Tests for Automatic Machine Translation Metrics with Adversarial Attacks

  Yichen Huang, Timothy Baldwin

• Medi-CAT: Contrastive Adversarial Training for Medical Image Classification

  Pervaiz Iqbal Khan, Andreas Dengel, Sheraz Ahmed

• Uncertainty quantification and out-of-distribution detection using surjective normalizing flows

  Simon Dirmeier, Ye Hong, Yanan Xin, Fernando Perez-Cruz

• NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks

  Seokil Ham, Jungwuk Park, Dong-Jun Han, Jaekyun Moon

2023-10-31

• Unmasking Bias and Inequities: A Systematic Review of Bias Detection and Mitigation in Healthcare Artificial Intelligence Using Electronic Health Records

  Feng Chen, Liqin Wang, Julie Hong, Jiaqi Jiang, Li Zhou

• Is Robustness Transferable across Languages in Multilingual Neural Machine Translation?

  Leiyu Pan, Supryadi, Deyi Xiong

• LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B

  Simon Lermen, Charlie Rogers-Smith, Jeffrey Ladish

• DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models

  Xinwei Wu, Junzhuo Li, Minghui Xu, Weilong Dong, Shuangzhi Wu, Chao Bian, Deyi Xiong

• Verification of Neural Networks Local Differential Classification Privacy

  Roie Reshef, Anan Kabaha, Olga Seleznova, Dana Drachsler-Cohen

• Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks

  Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher

2023-10-30

• PriPrune: Quantifying and Preserving Privacy in Pruned Federated Learning

  Tianyue Chu, Mengwei Yang, Nikolaos Laoutaris, Athina Markopoulou

• LipSim: A Provably Robust Perceptual Similarity Metric

  Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg

• Counterfactual Fairness for Predictions using Generative Adversarial Networks

  Yuchen Ma, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

2023-10-29

• Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method

  Yukun Zhao, Lingyong Yan, Weiwei Sun, Guoliang Xing, Chong Meng, Shuaiqiang Wang, Zhicong Cheng, Zhaochun Ren, Dawei Yin

• Fine tuning Pre trained Models for Robustness Under Noisy Labels

  Sumyeong Ahn, Sihyeon Kim, Jongwoo Ko, Se-Young Yun

• Adversarial Anomaly Detection using Gaussian Priors and Nonlinear Anomaly Scores

  Fiete Lüer, Tobias Weber, Maxim Dolgich, Christian Böhm

• $α$-Mutual Information: A Tunable Privacy Measure for Privacy Protection in Data Sharing

  MirHamed Jafarzadeh Asl, Mohammadhadi Shateri, Fabrice Labeau

• BlackJack: Secure machine learning on IoT devices through hardware-based shuffling

  Karthik Ganesan, Michal Fishkin, Ourong Lin, Natalie Enright Jerger

2023-10-27

• ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation

  Zi Lin, Zihan Wang, Yongqi Tong, Yangkun Wang, Yuxin Guo, Yujia Wang, Jingbo Shang

• Where you go is who you are -- A study on machine learning based semantic privacy attacks

  Nina Wiedemann, Ourania Kounadi, Martin Raubal, Krzysztof Janowicz

• A near-autonomous and incremental intrusion detection system through active learning of known and unknown attacks

  Lynda Boukela, Gongxuan Zhang, Meziane Yacoub, Samia Bouzefrane

2023-10-26

• CBD: A Certified Backdoor Detector Based on Local Dominant Probability

  Zhen Xiang, Zidi Xiong, Bo Li

• A Survey on Transferability of Adversarial Examples across Deep Neural Networks

  Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqain Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip Torr

• Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation

  Kira Maag, Asja Fischer

• Detecting stealthy cyberattacks on adaptive cruise control vehicles: A machine learning approach

  Tianyi Li, Mingfeng Shang, Shian Wang, Raphael Stern

• SoK: Pitfalls in Evaluating Black-Box Attacks

  Fnu Suya, Anshuman Suri, Tingwei Zhang, Jingtao Hong, Yuan Tian, David Evans

• Defending Against Transfer Attacks From Public Models

  Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David Wagner

• Proving Test Set Contamination in Black Box Language Models

  Yonatan Oren, Nicole Meister, Niladri Chatterji, Faisal Ladhak, Tatsunori B. Hashimoto

• Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow

  Erik Scheurer, Jenny Schmalfuss, Alexander Lis, Andrés Bruhn

2023-10-25

• Trust, but Verify: Robust Image Segmentation using Deep Learning

  Fahim Ahmed Zaman, Xiaodong Wu, Weiyu Xu, Milan Sonka, Raghuraman Mudumbai

• Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks

  Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel

• Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning

  Ananth Balashankar, Xiao Ma, Aradhana Sinha, Ahmad Beirami, Yao Qin, Jilin Chen, Alex Beutel

• Confounder Balancing in Adversarial Domain Adaptation for Pre-Trained Large Models Fine-Tuning

  Shuoran Jiang, Qingcai Chen, Yang Xiang, Youcheng Pan, Xiangping Wu

2023-10-24

• Enhancing Large Language Models for Secure Code Generation: A Dataset-driven Study on Vulnerability Mitigation

  Jiexin Wang, Liuwen Cao, Xitong Luo, Zhiping Zhou, Jiayuan Xie, Adam Jatowt, Yi Cai

• Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World

  Zhiling Zhang, Jie Zhang, Kui Zhang, Wenbo Zhou, Weiming Zhang, Nenghai Yu

• Defense Against Model Extraction Attacks on Recommender Systems

  Sixiao Zhang, Hongzhi Yin, Hongxu Chen, Cheng Long

• Robust and Actively Secure Serverless Collaborative Learning

  Olive Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang

• AI Hazard Management: A framework for the systematic management of root causes for AI risks

  Ronald Schnitzer, Andreas Hapfelmeier, Sven Gaube, Sonja Zillner

• FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering

  Md Rafi Ur Rashid, Vishnu Asutosh Dasu, Kang Gu, Najrin Sultana, Shagufta Mehnaz

• Poison is Not Traceless: Fully-Agnostic Detection of Poisoning Attacks

  Xinglong Chang, Katharina Dost, Gillian Dobbie, Jörg Wicker

• A model for multi-attack classification to improve intrusion detection performance using deep learning approaches

  Arun Kumar Silivery, Ram Mohan Rao Kovvur

2023-10-23

• 3D Masked Autoencoders for Enhanced Privacy in MRI Scans

  Lennart Alexander Van der Goten, Kevin Smith

• Self-Guard: Empower the LLM to Safeguard Itself

  Zezhong Wang, Fangkai Yang, Lu Wang, Pu Zhao, Hongru Wang, Liang Chen, Qingwei Lin, Kam-Fai Wong

• The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks

  Xiaoyi Chen, Siyuan Tang, Rui Zhu, Shijun Yan, Lei Jin, Zihao Wang, Liya Su, XiaoFeng Wang, Haixu Tang

• Deceptive Fairness Attacks on Graphs via Meta Learning

  Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong

• Momentum Gradient-based Untargeted Attack on Hypergraph Neural Networks

  Yang Chen, Stjepan Picek, Zhonglin Ye, Zhaoyang Wang, Haixing Zhao

2023-10-22

• Fundamental Limits of Membership Inference Attacks on Machine Learning Models

  Eric Aubinais, Elisabeth Gassiat, Pablo Piantanida

• Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models

  Shawn Shan, Wenxin Ding, Josephine Passananti, Haitao Zheng, Ben Y. Zhao

• MoPe: Model Perturbation-based Privacy Attacks on Language Models

  Marvin Li, Jason Wang, Jeffrey Wang, Seth Neel

• On existence, uniqueness and scalability of adversarial robustness measures for AI classifiers

  Illia Horenko

• AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models

  Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, Tong Sun

• Toward Stronger Textual Attack Detectors

  Pierre Colombo, Marine Picot, Nathan Noiry, Guillaume Staerman, Pablo Piantanida

• CT-GAT: Cross-Task Generative Adversarial Attack based on Transferability

  Minxuan Lv, Chengwei Dai, Kun Li, Wei Zhou, Songlin Hu

• Data-Free Knowledge Distillation Using Adversarially Perturbed OpenGL Shader Images

  Logan Frank, Jim Davis

• Bi-discriminator Domain Adversarial Neural Networks with Class-Level Gradient Alignment

  Chuang Zhao, Hongke Zhao, Hengshu Zhu, Zhenya Huang, Nan Feng, Enhong Chen, Hui Xiong

• ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency

  Minkyoung Cho, Yulong Cao, Zixiang Zhou, Z. Morley Mao

• F$^2$AT: Feature-Focusing Adversarial Training via Disentanglement of Natural and Perturbed Patterns

  Yaguan Qian, Chenyu Zhao, Zhaoquan Gu, Bin Wang, Shouling Ji, Wei Wang, Boyang Zhou, Pan Zhou

• Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrieval

  Xu Yuan, Zheng Zhang, Xunguang Wang, Lin Wu

• On the Detection of Image-Scaling Attacks in Machine Learning

  Erwin Quiring, Andreas Müller, Konrad Rieck

• Adversarial Attacks on Fairness of Graph Neural Networks

  Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li

• Competitive Advantage Attacks to Decentralized Federated Learning

  Yuqi Jia, Minghong Fang, Neil Zhenqiang Gong

• Enhancing Accuracy-Privacy Trade-off in Differentially Private Split Learning

  Ngoc Duy Pham, Khoa Tran Phan, Naveen Chilamkurti

2023-10-21

• GPT-4 Doesn't Know It's Wrong: An Analysis of Iterative Prompting for Reasoning Problems

  Kaya Stechly, Matthew Marquez, Subbarao Kambhampati

• Prompt Injection Attacks and Defenses in LLM-Integrated Applications

  Yupei Liu, Yuqi Jia, Runpeng Geng, Jinyuan Jia, Neil Zhenqiang Gong

• Probing LLMs for hate speech detection: strengths and vulnerabilities

  Sarthak Roy, Ashish Harshavardhan, Animesh Mukherjee, Punyajoy Saha

2023-10-20

• PoisonPrompt: Backdoor Attack on Prompt-based Large Language Models

  Hongwei Yao, Jian Lou, Zhan Qin

• Segment Anything Meets Universal Adversarial Perturbation

  Dongshen Han, Sheng Zheng, Chaoning Zhang

• Fast Model Debias with Machine Unlearning

  Ruizhe Chen, Jianfei Yang, Huimin Xiong, Jianhong Bai, Tianxiang Hu, Jin Hao, Yang Feng, Joey Tianyi Zhou, Jian Wu, Zuozhu Liu

2023-10-19

• Automatic Hallucination Assessment for Aligned Large Language Models via Transferable Adversarial Attacks

  Xiaodong Yu, Hao Cheng, Xiaodong Liu, Dan Roth, Jianfeng Gao

• Attack Prompt Generation for Red Teaming and Defending Large Language Models

  Boyi Deng, Wenjie Wang, Fuli Feng, Yang Deng, Qifan Wang, Xiangnan He

• Recoverable Privacy-Preserving Image Classification through Noise-like Adversarial Examples

  Jun Liu, Jiantao Zhou, Jinyu Tian, Weiwei Sun

• REVAMP: Automated Simulations of Adversarial Attacks on Arbitrary Objects in Realistic Scenes

  Matthew Hull, Zijie J. Wang, Duen Horng Chau

• Generating Robust Adversarial Examples against Online Social Networks (OSNs)

  Jun Liu, Jiantao Zhou, Haiwei Wu, Weiwei Sun, Jinyu Tian

• OODRobustBench: benchmarking and analyzing adversarial robustness under distribution shift

  Lin Li, Yifei Wang, Chawin Sitawarin, Michael Spratling

• CAT: Closed-loop Adversarial Training for Safe End-to-End Driving

  Linrui Zhang, Zhenghao Peng, Quanyi Li, Bolei Zhou

• Knowledge from Uncertainty in Evidential Deep Learning

  Cai Davies, Marc Roig Vilamala, Alun D. Preece, Federico Cerutti, Lance M. Kaplan, Supriyo Chakraborty

• Learn from the Past: A Proxy based Adversarial Defense Framework to Boost Robustness

  Yaohua Liu, Jiaxin Gao, Zhu Liu, Xianghao Jiao, Xin Fan, Risheng Liu

• PrivInfer: Privacy-Preserving Inference for Black-box Large Language Model

  Meng Tong, Kejiang Chen, Yuang Qi, Jie Zhang, Weiming Zhang, Nenghai Yu

• Privacy Preserving Large Language Models: ChatGPT Case Study Based Vision and Framework

  Imdad Ullah, Najm Hassan, Sukhpal Singh Gill, Basem Suleiman, Tariq Ahamed Ahanger, Zawar Shah, Junaid Qadir, Salil S. Kanhere

• SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models

  Boyang Zhang, Zheng Li, Ziqing Yang, Xinlei He, Michael Backes, Mario Fritz, Yang Zhang

2023-10-18

• Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning

  Taejin Kim, Jiarui Li, Shubhranshu Singh, Nikhil Madaan, Carlee Joe-Wong

• WaveAttack: Asymmetric Frequency Obfuscation-based Backdoor Attacks Against Deep Neural Networks

  Jun Xia, Zhihao Yue, Yingbo Zhou, Zhiwei Ling, Xian Wei, Mingsong Chen

• The Efficacy of Transformer-based Adversarial Attacks in Security Domains

  Kunyang Li, Kyle Domico, Jean-Charles Noirot Ferrand, Patrick McDaniel

• Black-Box Training Data Identification in GANs via Detector Networks

  Lukman Olagoke, Salil Vadhan, Seth Neel

• A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses

  Caelin G. Kaplan, Chuan Xu, Othmane Marfoq, Giovanni Neglia, Anderson Santana de Oliveira

• Domain-Generalized Face Anti-Spoofing with Unknown Attacks

  Zong-Wei Hong, Yu-Chen Lin, Hsuan-Tung Liu, Yi-Ren Yeh, Chu-Song Chen

• To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now

  Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu

• Exploring Decision-based Black-box Attacks on Face Forgery Detection

  Zhaoyu Chen, Bo Li, Kaixun Jiang, Shuang Wu, Shouhong Ding, Wenqiang Zhang

• Revisiting Transferable Adversarial Image Examples: Attack Categorization, Evaluation Guidelines, and New Insights

  Zhengyu Zhao, Hanwei Zhang, Renjue Li, Ronan Sicre, Laurent Amsaleg, Michael Backes, Qi Li, Chao Shen

• In defense of parameter sharing for model-compression

  Aditya Desai, Anshumali Shrivastava

• Adversarial Training for Physics-Informed Neural Networks

  Yao Li, Shengzhu Shi, Zhichang Guo, Boying Wu

• Quantifying Privacy Risks of Prompts in Visual Prompt Learning

  Yixin Wu, Rui Wen, Michael Backes, Pascal Berrang, Mathias Humbert, Yun Shen, Yang Zhang

2023-10-17

• Demystifying Poisoning Backdoor Attacks from a Statistical Perspective

  Xun Xian, Ganghua Wang, Jayanth Srinivasa, Ashish Kundu, Xuan Bi, Mingyi Hong, Jie Ding

• Learning from Red Teaming: Gender Bias Provocation and Mitigation in Large Language Models

  Hsuan Su, Cheng-Chu Cheng, Hua Farn, Shachi H Kumar, Saurav Sahay, Shang-Tse Chen, Hung-yi Lee

• Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting

  Melanie Sclar, Yejin Choi, Yulia Tsvetkov, Alane Suhr

• Functional Invariants to Watermark Large Transformers

  Fernandez Pierre, Couairon Guillaume, Furon Teddy, Douze Matthijs

• Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks

  Jiaying Wu, Bryan Hooi

• Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

  Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, Pedram Zaree, Yue Dong, Nael Abu-Ghazaleh

• Will the Prince Get True Love's Kiss? On the Model Sensitivity to Gender Perturbation over Fairytale Texts

  Christina Chance, Da Yin, Dakuo Wang, Kai-Wei Chang

• Backdoor Attack through Machine Unlearning

  Peixin Zhang, Jun Sun, Mingtian Tan, Xinyu Wang

• Regularization properties of adversarially-trained linear regression

  Antônio H. Ribeiro, Dave Zachariah, Francis Bach, Thomas B. Schön

• Locally Differentially Private Graph Embedding

  Zening Li, Rong-Hua Li, Meihao Liao, Fusheng Jin, Guoren Wang

• Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning

  Rui Wen, Tianhao Wang, Michael Backes, Yang Zhang, Ahmed Salem

• Unbiased Watermark for Large Language Models

  Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang

2023-10-16

• DANAA: Towards transferable attacks with double adversarial neuron attribution

  Zhibo Jin, Zhiyu Zhu, Xinyi Wang, Jiayu Zhang, Jun Shen, Huaming Chen

• Privacy in Large Language Models: Attacks, Defenses and Future Directions

  Haoran Li, Yulin Chen, Jinglong Luo, Yan Kang, Xiaojin Zhang, Qi Hu, Chunkit Chan, Yangqiu Song

• Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

  Shuyu Jiang, Xingshu Chen, Rui Tang

• ASSERT: Automated Safety Scenario Red Teaming for Evaluating the Robustness of Large Language Models

  Alex Mei, Sharon Levy, William Yang Wang

• Orthogonal Uncertainty Representation of Data Manifold for Robust Long-Tailed Learning

  Yanbiao Ma, Licheng Jiao, Fang Liu, Shuyuan Yang, Xu Liu, Lingling Li

• Quantifying Assistive Robustness Via the Natural-Adversarial Frontier

  Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Anca D. Dragan

2023-10-15

• SCME: A Self-Contrastive Method for Data-free and Query-Limited Model Extraction Attack

  Renyang Liu, Jinhong Zhang, Kwok-Yan Lam, Jun Zhao, Wei Zhou

• AFLOW: Developing Adversarial Examples under Extremely Noise-limited Settings

  Renyang Liu, Jinhong Zhang, Haoran Li, Jin Zhang, Yuanyu Wang, Wei Zhou

• Black-box Targeted Adversarial Attack on Segment Anything (SAM)

  Sheng Zheng, Chaoning Zhang

• Explore the Effect of Data Selection on Poison Efficiency in Backdoor Attacks

  Ziqiang Li, Pengfei Xia, Hong Sun, Yueqi Zeng, Wei Zhang, Bin Li

• Model Inversion Attacks on Homogeneous and Heterogeneous Graph Neural Networks

  Renyang Liu, Wei Zhou, Jinhong Zhang, Xiaoyuan Liu, Peiyuan Si, Haoran Li

• Evaluating Robustness of Visual Representations for Object Assembly Task Requiring Spatio-Geometrical Reasoning

  Chahyon Ku, Carl Winge, Ryan Diaz, Wentao Yuan, Karthik Desingh

• Is Certifying $\ell_p$ Robustness Still Worthwhile?

  Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu, Weicheng Yu, Corina Pasareanu, Anupam Datta, Matt Fredrikson

• MAGIC: Detecting Advanced Persistent Threats via Masked Graph Representation Learning

  Zian Jia, Yun Xiong, Yuhong Nan, Yao Zhang, Jinjing Zhao, Mi Wen

• A Comprehensive Study of Privacy Risks in Curriculum Learning

  Joann Qiongna Chen, Xinlei He, Zheng Li, Yang Zhang, Zhou Li

• Prime Match: A Privacy-Preserving Inventory Matching System

  Antigoni Polychroniadou, Gilad Asharov, Benjamin Diamond, Tucker Balch, Hans Buehler, Richard Hua, Suwen Gu, Greg Gimler, Manuela Veloso

• BufferSearch: Generating Black-Box Adversarial Texts With Lower Queries

  Wenjie Lv, Zhen Wang, Yitao Zheng, Zhehua Zhong, Qi Xuan, Tianyi Chen

2023-10-14

• Defending Our Privacy With Backdoors

  Dominik Hintersdorf, Lukas Struppek, Daniel Neider, Kristian Kersting

• Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks

  Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio

2023-10-13

• Towards the Vulnerability of Watermarking Artificial Intelligence Generated Content

  Guanlin Li, Yifei Chen, Jie Zhang, Jiwei Li, Shangwei Guo, Tianwei Zhang

• Sentinel: An Aggregation Function to Secure Decentralized Federated Learning

  Chao Feng, Alberto Huertas Celdran, Janosch Baltensperger, Enrique Tomas Matınez Bertran, Gerome Bovet, Burkhard Stiller

• Trustworthy Machine Learning

  Bálint Mucsányi, Michael Kirchhof, Elisa Nguyen, Alexander Rubinstein, Seong Joon Oh

• Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders

  Jan Dubiński, Stanisław Pawlak, Franziska Boenisch, Tomasz Trzciński, Adam Dziedzic

2023-10-12

• Effects of Human Adversarial and Affable Samples on BERT Generalizability

  Aparna Elangovan, Jiayuan He, Yuan Li, Karin Verspoor

• Concealed Electronic Countermeasures of Radar Signal with Adversarial Examples

  Ruinan Ma, Canjie Zhu, Mingfeng Lu, Yunjie Li, Yu-an Tan, Ruibin Zhang, Ran Tao

• Jailbreaking Black Box Large Language Models in Twenty Queries

  Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, Eric Wong

• Towards Robust Multi-Modal Reasoning via Model Selection

  Xiangyan Liu, Rongxue Li, Wei Ji, Tao Lin

• Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization

  Giuseppe Floris, Raffaele Mura, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio

• Invisible Threats: Backdoor Attack in OCR Systems

  Mauro Conti, Nicola Farronato, Stefanos Koffas, Luca Pajola, Stjepan Picek

• Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches

  Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng

• Towards Causal Deep Learning for Vulnerability Detection

  Md Mahbubur Rahman, Ira Ceka, Chengzhi Mao, Saikat Chakraborty, Baishakhi Ray, Wei Le

2023-10-11

• RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems

  Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda

• Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic Classification

  Mahmoud Nazzal, Nura Aljaafari, Ahmed Sawalmeh, Abdallah Khreishah, Muhammad Anan, Abdulelah Algosaibi, Mohammed Alnaeem, Adel Aldalbahi, Abdulaziz Alhumam, Conrado P. Vizcarra, Shadan Alhamed

• Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation

  Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen

• No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML

  Ziqi Zhang, Chen Gong, Yifeng Cai, Yuanyuan Yuan, Bingyan Liu, Ding Li, Yao Guo, Xiangqun Chen

• Boosting Black-box Attack to Deep Neural Networks with Conditional Diffusion Models

  Renyang Liu, Wei Zhou, Tianwei Zhang, Kangjie Chen, Jun Zhao, Kwok-Yan Lam

• Composite Backdoor Attacks Against Large Language Models

  Hai Huang, Zhengyu Zhao, Michael Backes, Yun Shen, Yang Zhang

• Comparing the robustness of modern no-reference image- and video-quality metrics to adversarial attacks

  Anastasia Antsiferova, Khaled Abud, Aleksandr Gushchin, Sergey Lavrushkin, Ekaterina Shumitskaya, Maksim Velikanov, Dmitriy Vatolin

• Robust Safe Reinforcement Learning under Adversarial Disturbances

  Zeyang Li, Chuxiong Hu, Shengbo Eben Li, Jia Cheng, Yunan Wang

2023-10-10

• Fingerprint Attack: Client De-Anonymization in Federated Learning

  Qiongkai Xu, Trevor Cohn, Olga Ohrimenko

• Suppressing Overestimation in Q-Learning through Adversarial Behaviors

  HyeAnn Lee, Donghwan Lee

• Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

  Zeming Wei, Yifei Wang, Yisen Wang

• Multilingual Jailbreak Challenges in Large Language Models

  Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, Lidong Bing

• A Semantic Invariant Robust Watermark for Large Language Models

  Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, Lijie Wen

• Adversarial Masked Image Inpainting for Robust Detection of Mpox and Non-Mpox

  Yubiao Yue, Zhenzhang Li

• Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data

  Lukas Struppek, Martin B. Hentschel, Clifton Poth, Dominik Hintersdorf, Kristian Kersting

• Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks

  Lukas Struppek, Dominik Hintersdorf, Kristian Kersting

• Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach

  Shaopeng Fu, Di Wang

• PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization

  Jiancong Xiao, Ruoyu Sun, Zhi-quan Luo

• Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach

  Kai Zhao, Qiyu Kang, Yang Song, Rui She, Sijie Wang, Wee Peng Tay

• Exploring adversarial attacks in federated learning for medical imaging

  Erfan Darzi, Florian Dubost, N.M. Sijtsema, P.M.A van Ooijen

2023-10-09

• The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

  Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S.M Towhidul Islam Tonmoy, Aman Chadha, Amit P. Sheth, Amitava Das

• Large Language Models Can Be Good Privacy Protection Learners

  Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Haifeng Chen, Wei Wang, Wei Cheng

• LoFT: Local Proxy Fine-tuning For Improving Transferability Of Adversarial Attacks Against Large Language Model

  Muhammad Ahmed Shah, Roshan Sharma, Hira Dhamyal, Raphael Olivier, Ankit Shah, Dareen Alharthi, Hazim T Bukhari, Massa Baali, Soham Deshmukh, Michael Kuhlmann, Bhiksha Raj, Rita Singh

• AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

  Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao

• Understanding and Improving Adversarial Attacks on Latent Diffusion Model

  Boyang Zheng, Chumeng Liang, Xiaoyu Wu, Yan Liu

• Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization

  Zexu Sun, Bowei He, Ming Ma, Jiakai Tang, Yuchen Wang, Chen Ma, Dugang Liu

• Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks

  Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman

• BRAINTEASER: Lateral Thinking Puzzles for Large Language Model

  Yifan Jiang, Filip Ilievski, Kaixin Ma

• Do Large Language Models Know about Facts?

  Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S. Yu, Zhijiang Guo

• SC-Safety: A Multi-round Open-ended Question Adversarial Safety Benchmark for Large Language Models in Chinese

  Liang Xu, Kangkang Zhao, Lei Zhu, Hang Xue

• IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers

  Zhenglin Huang, Xianan Bao, Na Zhang, Qingqi Zhang, Xiaomei Tu, Biao Wu, Xi Yang

• VLAttack: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models

  Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma

• GReAT: A Graph Regularized Adversarial Training Method

  Samet Bayram, Kenneth Barner

• Generating Less Certain Adversarial Examples Improves Robust Generalization

  Minxing Zhang, Michael Backes, Xiao Zhang

• Protecting Sensitive Data through Federated Co-Training

  Amr Abourayya, Jens Kleesiek, Kanishka Rao, Erman Ayday, Bharat Rao, Geoff Webb, Michael Kamp

• Tight Certified Robustness via Min-Max Representations of ReLU Neural Networks

  Brendon G. Anderson, Samuel Pfrommer, Somayeh Sojoudi

2023-10-08

• Lightweight Boosting Models for User Response Prediction Using Adversarial Validation

  Hyeonwoo Kim, Wonsung Lee

• Assessing Robustness via Score-Based Adversarial Image Generation

  Marcel Kollovieh, Lukas Gosch, Yan Scholten, Marten Lienen, Stephan Günnemann

• Indirect Meltdown: Building Novel Side-Channel Attacks from Transient-Execution Attacks

  Daniel Weber, Fabian Thomas, Lukas Gerlach, Ruiyi Zhang, Michael Schwarz

2023-10-07

• Benchmarking Local Robustness of High-Accuracy Binary Neural Networks for Enhanced Traffic Sign Recognition

  Andreea Postovan, Mădălina Eraşcu

• Efficient Federated Prompt Tuning for Black-box Large Pre-trained Models

  Zihao Lin, Yan Sun, Yifan Shi, Xueqian Wang, Lifu Huang, Li Shen, Dacheng Tao

• Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

  Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson

• Ask for Alice: Online Covert Distress Signal in the Presence of a Strong Adversary

  Hayyu Imanda, Kasper Rasmussen

2023-10-06

• Misusing Tools in Large Language Models With Visual Adversarial Examples

  Xiaohan Fu, Zihan Wang, Shuheng Li, Rajesh K. Gupta, Niloofar Mireshghallah, Taylor Berg-Kirkpatrick, Earlence Fernandes

• Robust Representation Learning via Asymmetric Negative Contrast and Reverse Attention

  Nuoyan Zhou, Decheng Liu, Dawei Zhou, Xinbo Gao, Nannan Wang

• SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks

  Alexander Robey, Eric Wong, Hamed Hassani, George J. Pappas

• A Formalism and Approach for Improving Robustness of Large Language Models Using Risk-Adjusted Confidence Scores

  Ke Shen, Mayank Kejriwal

• Shielding the Unseen: Privacy Protection through Poisoning NeRF with Spatial Deformation

  Yihan Wu, Brandon Y. Feng, Heng Huang

• CSI: Enhancing the Robustness of 3D Point Cloud Recognition against Corruption

  Zhuoyuan Wu, Jiachen Sun, Chaowei Xiao

• OMG-ATTACK: Self-Supervised On-Manifold Generation of Transferable Evasion Attacks

  Ofir Bar Tal, Adi Haviv, Amit H. Bermano

• Untargeted White-box Adversarial Attack with Heuristic Defence Methods in Real-time Deep Learning based Network Intrusion Detection System

  Khushnaseeb Roshan, Aasim Zafar, Sheikh Burhan Ul Haque

• Targeted Adversarial Attacks on Generalizable Neural Radiance Fields

  Andras Horvath, Csaba M. Jozsa

• Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally

  Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali, Mohamed Abdallah, Junaid Qadir, Dinh Thai Hoang, Dusit Niyato, Ala Al-Fuqaha

• Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors

  Biagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio

• Regret Analysis of Distributed Online Control for LTI Systems with Adversarial Disturbances

  Ting-Jui Chang, Shahin Shahrampour

• Certifiably Robust Graph Contrastive Learning

  Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang

• An Integrated Algorithm for Robust and Imperceptible Audio Adversarial Examples

  Armin Ettenhofer, Jan-Philipp Schulze, Karla Pizzi

2023-10-05

• Low-Resource Languages Jailbreak GPT-4

  Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach

• Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design

  Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster

• Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models

  Xianjun Yang, Xiao Wang, Qi Zhang, Linda Petzold, William Yang Wang, Xun Zhao, Dahua Lin

• Can Large Language Models Provide Security & Privacy Advice? Measuring the Ability of LLMs to Refute Misconceptions

  Yufan Chen, Arjun Arunasalam, Z. Berkay Celik

• SlowFormer: Universal Adversarial Patch for Attack on Compute and Energy Efficiency of Inference Efficient Vision Transformers

  KL Navaneet, Soroush Abbasi Koohpayegani, Essam Sleiman, Hamed Pirsiavash

• Splitting the Difference on Adversarial Training

  Matan Levi, Aryeh Kontorovich

• A Recipe for Improved Certifiable Robustness: Capacity and Data

  Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson

• Jailbreaker in Jail: Moving Target Defense for Large Language Models

  Bocheng Chen, Advait Paliwal, Qiben Yan

2023-10-04

• Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey

  Victoria Smith, Ali Shahin Shamsabadi, Carolyn Ashurst, Adrian Weller

• Fooling the Textual Fooler via Randomizing Latent Representations

  Duy C. Hoang, Quang H. Nguyen, Saurav Manchanda, MinLong Peng, Kok-Seng Wong, Khoa D. Doan

• On the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused?

  Hangfan Zhang, Zhimeng Guo, Huaisheng Zhu, Bochuan Cao, Lu Lin, Jinyuan Jia, Jinghui Chen, Dinghao Wu

• Towards Stable Backdoor Purification through Feature Shift Tuning

  Rui Min, Zeyu Qin, Li Shen, Minhao Cheng

• Defending Against Authorship Identification Attacks

  Haining Wang

• Can Language Models be Instructed to Protect Personal Information?

  Yang Chen, Ethan Mendes, Sauvik Das, Wei Xu, Alan Ritter

• Adversarial Client Detection via Non-parametric Subspace Monitoring in the Internet of Federated Things

  Xianjian Xie, Xiaochen Xian, Dan Li, Andi Wang

• Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations

  Yongshuo Zong, Tingyang Yu, Bingchen Zhao, Ruchika Chavhan, Timothy Hospedales

• Beyond Labeling Oracles: What does it mean to steal ML models?

  Avital Shafran, Ilia Shumailov, Murat A. Erdogdu, Nicolas Papernot

• FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks

  Jorge Castillo, Phillip Rieger, Hossein Fereidooni, Qian Chen, Ahmad Sadeghi

• Waveform Manipulation Against DNN-based Modulation Classification Attacks

  Dimitrios Varkatzas, Antonios Argyriou

2023-10-03

• Adversarial Driving Behavior Generation Incorporating Human Risk Cognition for Autonomous Vehicle Evaluation

  Zhen Liu, Hang Gao, Hao Ma, Shuo Cai, Yunfeng Hu, Ting Qu, Hong Chen, Xun Gong

• Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization

  Mahyar Fazlyab, Taha Entesari, Aniket Roy, Rama Chellappa

• Beyond Random Noise: Insights on Anonymization Strategies from a Latent Bandit Study

  Alexander Galozy, Sadi Alawadi, Victor Kebande, Sławomir Nowaczyk

• Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks

  Quang H. Nguyen, Yingjie Lao, Tung Pham, Kok-Seng Wong, Khoa D. Doan

• Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals

  Yair Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart

• A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks

  Yanjie Li, Bin Xie, Songtao Guo, Yuanyuan Yang, Bin Xiao

• All Languages Matter: On the Multilingual Safety of Large Language Models

  Wenxuan Wang, Zhaopeng Tu, Chang Chen, Youliang Yuan, Jen-tse Huang, Wenxiang Jiao, Michael R. Lyu

• Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives

  Sihao Hu, Tiansheng Huang, Fatih İlhan, Selim Fukan Tekin, Ling Liu

• Red Teaming Game: A Game-Theoretic Framework for Red Teaming Language Models

  Chengdong Ma, Ziran Yang, Minquan Gao, Hai Ci, Jun Gao, Xuehai Pan, Yaodong Yang

• Fewer is More: Trojan Attacks on Parameter-Efficient Fine-Tuning

  Lauren Hong, Ting Wang

• Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks

  Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Chegini, Wenxiao Wang, Soheil Feizi

• Human-Producible Adversarial Examples

  David Khachaturov, Yue Gao, Ilia Shumailov, Robert Mullins, Ross Anderson, Kassem Fawaz

• Black-box Attacks on Image Activity Prediction and its Natural Language Explanations

  Alina Elena Baia, Valentina Poggioni, Andrea Cavallaro

• GhostEncoder: Stealthy Backdoor Attacks with Dynamic Triggers to Pre-trained Encoders in Self-supervised Learning

  Qiannan Wang, Changchun Yin, Zhe Liu, Liming Fang, Run Wang, Chenhao Lin

• Counterfactual Image Generation for adversarially robust and interpretable Classifiers

  Rafael Bischof, Florian Scheidegger, Michael A. Kraus, A. Cristiano I. Malossi

• Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study

  Myeongseob Ko, Ming Jin, Chenguang Wang, Ruoxi Jia

• Understanding Adversarial Transferability in Federated Learning

  Yijiang Li, Ying Gao, Haohan Wang

• On the Onset of Robust Overfitting in Adversarial Training

  Chaojian Yu, Xiaolong Shi, Jun Yu, Bo Han, Tongliang Liu

• Balancing Efficiency vs. Effectiveness and Providing Missing Label Robustness in Multi-Label Stream Classification

  Sepehr Bakhshi, Fazli Can

• Adversarial Explainability: Utilizing Explainable Machine Learning in Bypassing IoT Botnet Detection Systems

  Mohammed M. Alani, Atefeh Mashatan, Ali Miri

• Source Inference Attacks: Beyond Membership Inference Attacks in Federated Learning

  Hongsheng Hu, Xuyun Zhang, Zoran Salcic, Lichao Sun, Kim-Kwang Raymond Choo, Gillian Dobbie

2023-10-02

• AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recovery

  Jinyin Chen, Jie Ge, Shilian Zheng, Linhui Ye, Haibin Zheng, Weiguo Shen, Keqiang Yue, Xiaoniu Yang

• General Lipschitz: Certified Robustness Against Resolvable Semantic Transformations via Transformation-Dependent Randomized Smoothing

  Dmitrii Korzh, Mikhail Pautov, Olga Tsymboi, Ivan Oseledets

• Investigating Human-Identifiable Features Hidden in Adversarial Perturbations

  Dennis Y. Menn, Tzu-hsun Feng, Sriram Vishwanath, Hung-yi Lee

• Medical Foundation Models are Susceptible to Targeted Misinformation Attacks

  Tianyu Han, Sven Nebelung, Firas Khader, Tianci Wang, Gustav Mueller-Franzes, Christiane Kuhl, Sebastian Försch, Jens Kleesiek, Christoph Haarburger, Keno K. Bressem, Jakob Nikolas Kather, Daniel Truhn

• Adversarial Machine Learning in Latent Representations of Neural Networks

  Milin Zhang, Mohammad Abdi, Francesco Restuccia

• Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks

  Vaidehi Patil, Peter Hase, Mohit Bansal

• LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud

  Mengke Zhang, Tianxing He, Tianle Wang, Fatemehsadat Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov

• Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness

  Xiaoyu Wen, Xudong Yu, Rui Yang, Chenjia Bai, Zhen Wang

• Efficient Biologically Plausible Adversarial Training

  Matilde Tristany Farinha, Thomas Ortner, Giorgia Dellaferrera, Benjamin Grewe, Angeliki Pantazi

• Adversarial Imitation Learning from Visual Observations using Latent Information

  Vittorio Giammarino, James Queeney, Ioannis Ch. Paschalidis

2023-10-01

• Towards Efficient and Trustworthy AI Through Hardware-Algorithm-Communication Co-Design

  Bipin Rajendran, Osvaldo Simeone, Bashir M. Al-Hashimi

• VDC: Versatile Data Cleanser for Detecting Dirty Samples via Visual-Linguistic Inconsistency

  Zihao Zhu, Mingda Zhang, Shaokui Wei, Bingzhe Wu, Baoyuan Wu

2023-09-30

• Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey

  Lea Demelius, Roman Kern, Andreas Trügler

• Robust Offline Reinforcement Learning -- Certify the Confidence Interval

  Jiarui Yao, Simon Shaolei Du

2023-09-29

• Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness

  Ambar Pal, Jeremias Sulam, René Vidal

• Parameter-Saving Adversarial Training: Reinforcing Multi-Perturbation Robustness via Hypernetworks

  Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu

• On the Trade-offs between Adversarial Robustness and Actionable Explanations

  Satyapriya Krishna, Chirag Agarwal, Himabindu Lakkaraju

• Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective

  Zhen Qin, Feiyi Chen, Chen Zhi, Xueqiang Yan, Shuiguang Deng

• Towards Poisoning Fair Representations

  Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao

• Compilation as a Defense: Enhancing DL Model Attack Robustness via Tensor Optimization

  Stefan Trawicki, William Hackett, Lewis Birch, Neeraj Suri, Peter Garraghan

• Cyber Sentinel: Exploring Conversational Agents in Streamlining Security Tasks with GPT-4

  Mehrdad Kaheh, Danial Khosh Kholgh, Panos Kostakos

2023-09-28

• How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions

  Lorenzo Pacchiardi, Alex J. Chan, Sören Mindermann, Ilan Moscovitz, Alexa Y. Pan, Yarin Gal, Owain Evans, Jan Brauner

• The Robust Semantic Segmentation UNCV2023 Challenge Results

  Xuanlong Yu, Yi Zuo, Zitao Wang, Xiaowen Zhang, Jiaxuan Zhao, Yuting Yang, Licheng Jiao, Rui Peng, Xinyi Wang, Junpei Zhang, Kexin Zhang, Fang Liu, Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo, Hanlin Tian, Kenta Matsui, Tianhao Wang, Fahmy Adan, Zhitong Gao, Xuming He, Quentin Bouniot, Hossein Moghaddam, Shyam Nandan Rai, Fabio Cermelli, Carlo Masone, Andrea Pilzer, Elisa Ricci, Andrei Bursuc, Arno Solin, Martin Trapp, Rui Li, Angela Yao, Wenlong Chen, Ivor Simpson, Neill D. F. Campbell, Gianni Franchi

• A Unified View of Differentially Private Deep Generative Modeling

  Dingfan Chen, Raouf Kerkouche, Mario Fritz

• On Computational Entanglement and Its Interpretation in Adversarial Machine Learning

  YenLung Lai, Xingbo Dong, Zhe Jin

• Automatic Feature Fairness in Recommendation via Adversaries

  Hengchang Hu, Yiming Cao, Zhankui He, Samson Tan, Min-Yen Kan

2023-09-27

• Bias Assessment and Mitigation in LLM-based Code Generation

  Dong Huang, Qingwen Bu, Jie Zhang, Xiaofei Xie, Junjie Chen, Heming Cui

• Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM

  Bochuan Cao, Yuanpu Cao, Lu Lin, Jinghui Chen

• Survey of Social Bias in Vision-Language Models

  Nayeon Lee, Yejin Bang, Holy Lovenia, Samuel Cahyawijaya, Wenliang Dai, Pascale Fung

• XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection

  Vu Le Anh Quan, Chau Thuan Phat, Kiet Van Nguyen, Phan The Duy, Van-Hau Pham

• DifAttack: Query-Efficient Black-Box Attack via Disentangled Feature Space

  Liu Jun, Zhou Jiantao, Zeng Jiandian, Jinyu Tian

• Structure Invariant Transformation for better Adversarial Transferability

  Xiaosen Wang, Zeliang Zhang, Jianping Zhang

• Frugal Satellite Image Change Detection with Deep-Net Inversion

  Hichem Sahbi, Sebastien Deschamps

• The Surveillance AI Pipeline

  Pratyusha Ria Kalluri, William Agnew, Myra Cheng, Kentrell Owens, Luca Soldaini, Abeba Birhane

• Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction

  Yuning Du, Yuyang Xue, Rohan Dharmakumar, Sotirios A. Tsaftaris

• LogGPT: Log Anomaly Detection via GPT

  Xiao Han, Shuhan Yuan, Mohamed Trabelsi

• Privacy-preserving and Privacy-attacking Approaches for Speech and Audio -- A Survey

  Yuchen Liu, Apu Kapadia, Donald Williamson

2023-09-26

• Investigating Efficient Deep Learning Architectures For Side-Channel Attacks on AES

  Yohaï-Eliel Berreby, Laurent Sauvage

• Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation

  Kai Huang, Hanyun Yin, Heng Huang, Wei Gao

• Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks

  Zhaohan Xi, Tianyu Du, Changjiang Li, Ren Pang, Shouling Ji, Jinghui Chen, Fenglong Ma, Ting Wang

• LLMs as Counterfactual Explanation Modules: Can ChatGPT Explain Black-box Text Classifiers?

  Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, Huan Liu

• Seeing Is Not Always Believing: Invisible Collision Attack and Defence on Pre-Trained Models

  Minghang Deng, Zhong Zhang, Junming Shao

• PRIS: Practical robust invertible network for image steganography

  Hang Yang, Yitian Xu, Xuhua Liu, Xiaodong Ma

• GHN-QAT: Training Graph Hypernetworks to Predict Quantization-Robust Parameters of Unseen Limited Precision Neural Networks

  Stone Yun, Alexander Wong

• Can LLM-Generated Misinformation Be Detected?

  Canyu Chen, Kai Shu

• RBFormer: Improve Adversarial Robustness of Transformer by Robust Bias

  Hao Cheng, Jinhao Duan, Hui Li, Lyutianyang Zhang, Jiahang Cao, Ping Wang, Jize Zhang, Kaidi Xu, Renjing Xu

• DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning

  Kangyang Luo, Shuai Wang, Yexuan Fu, Xiang Li, Yunshi Lan, Ming Gao

• Vulnerabilities in Video Quality Assessment Models: The Challenge of Adversarial Attacks

  Ao-Xiang Zhang, Yu Ran, Weixuan Tang, Yuan-Gen Wang

• Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagation

  Yijun Yang, Angelica I. Aviles-Rivero, Huazhu Fu, Ye Liu, Weiming Wang, Lei Zhu

• Combining Two Adversarial Attacks Against Person Re-Identification Systems

  Eduardo de O. Andrade, Igor Garcia Ballhausen Sampaio, Joris Guérin, José Viterbo

• Adversarial Attacks on Video Object Segmentation with Hard Region Discovery

  Ping Li, Yu Zhang, Li Yuan, Jian Zhao, Xianghua Xu, Xiaoqin Zhang

• SurrogatePrompt: Bypassing the Safety Filter of Text-To-Image Models via Substitution

  Zhongjie Ba, Jieming Zhong, Jiachen Lei, Peng Cheng, Qinglong Wang, Zhan Qin, Zhibo Wang, Kui Ren

• Spatial-frequency channels, shape bias, and adversarial robustness

  Ajay Subramanian, Elena Sizikova, Najib J. Majaj, Denis G. Pelli

• Beyond Fairness: Age-Harmless Parkinson's Detection via Voice

  Yicheng Wang, Xiaotian Han, Leisheng Yu, Na Zou

• Improving Robustness of Deep Convolutional Neural Networks via Multiresolution Learning

  Hongyan Zhou, Yao Liang

• Invisible Watermarking for Audio Generation Diffusion Models

  Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng, Wenqi Wei

• On the Effectiveness of Adversarial Samples against Ensemble Learning-based Windows PE Malware Detectors

  Trong-Nghia To, Danh Le Kim, Do Thi Thu Hien, Nghi Hoang Khoa, Hien Do Hoang, Phan The Duy, Van-Hau Pham

2023-09-25

• Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation

  Junqi Jiang, Jianglin Lan, Francesco Leofante, Antonio Rago, Francesca Toni

• HANS, are you clever? Clever Hans Effect Analysis of Neural Systems

  Leonardo Ranaldi, Fabio Massimo Zanzotto

• Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception?

  Xiaoxiao Sun, Nidham Gazagnadou, Vivek Sharma, Lingjuan Lyu, Hongdong Li, Liang Zheng

• Improving Machine Learning Robustness via Adversarial Training

  Long Dang, Thushari Hapuarachchi, Kaiqi Xiong, Jing Lin

• On Data Fabrication in Collaborative Vehicular Perception: Attacks and Countermeasures

  Qingzhao Zhang, Shuowei Jin, Jiachen Sun, Xumiao Zhang, Ruiyang Zhu, Qi Alfred Chen, Z. Morley Mao

• Robotic Handling of Compliant Food Objects by Robust Learning from Demonstration

  Ekrem Misimi, Alexander Olofsson, Aleksander Eilertsen, Elling Ruud Øye, John Reidar Mathiassen

2023-09-24

• Distilling Adversarial Prompts from Safety Benchmarks: Report for the Adversarial Nibbler Challenge

  Manuel Brack, Patrick Schramowski, Kristian Kersting

• The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"

  Lukas Berglund, Meg Tong, Max Kaufmann, Mikita Balesni, Asa Cooper Stickland, Tomasz Korbak, Owain Evans

2023-09-23

• Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection

  Beizhe Hu, Qiang Sheng, Juan Cao, Yuhui Shi, Yang Li, Danding Wang, Peng Qi

• A Chinese Prompt Attack Dataset for LLMs with Evil Content

  Chengyuan Liu, Fubang Zhao, Lizhi Qing, Yangyang Kang, Changlong Sun, Kun Kuang, Fei Wu

• Vulnerability of 3D Face Recognition Systems to Morphing Attacks

  Sanjeet Vardam, Luuk Spreeuwers

• Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach

  Wentao Hu, Hui Fang

2023-09-22

• CATS: Conditional Adversarial Trajectory Synthesis for Privacy-Preserving Trajectory Data Publication Using Deep Learning Approaches

  Jinmeng Rao, Song Gao, Sijia Zhu

• How Robust is Google's Bard to Adversarial Image Attacks?

  Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, Xiao Yang, Yichi Zhang, Yu Tian, Hang Su, Jun Zhu

• Knowledge Sanitization of Large Language Models

  Yoichi Ishibashi, Hidetoshi Shimodaira

• On the Relationship between Skill Neurons and Robustness in Prompt Tuning

  Leon Ackermann, Xenia Ohmer

• TextCLIP: Text-Guided Face Image Generation And Manipulation Without Adversarial Training

  Xiaozhou You, Jian Zhang

• Dictionary Attack on IMU-based Gait Authentication

  Rajesh Kumar, Can Isik, Chilukuri K. Mohan

• Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation

  Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim

• MarkNerf:Watermarking for Neural Radiance Field

  Lifeng Chen, Jia Liu, Yan Ke, Wenquan Sun, Weina Dong, Xiaozhong Pan

• DeepTheft: Stealing DNN Model Architectures through Power Side Channel

  Yansong Gao, Huming Qiu, Zhi Zhang, Binghui Wang, Hua Ma, Alsharif Abuadbba, Minhui Xue, Anmin Fu, Surya Nepal

2023-09-21

• When to Trust AI: Advances and Challenges for Certification of Neural Networks

  Marta Kwiatkowska, Xiyue Zhang

• C$\cdot$ASE: Learning Conditional Adversarial Skill Embeddings for Physics-based Characters

  Zhiyang Dou, Xuelin Chen, Qingnan Fan, Taku Komura, Wenping Wang

• What Learned Representations and Influence Functions Can Tell Us About Adversarial Examples

  Shakila Mahjabin Tonni, Mark Dras

• PRAT: PRofiling Adversarial aTtacks

  Rahul Ambati, Naveed Akhtar, Ajmal Mian, Yogesh Singh Rawat

• It's Simplex! Disaggregating Measures to Improve Certified Robustness

  Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I.P. Rubinstein

• Learning Patient Static Information from Time-series EHR and an Approach for Safeguarding Privacy and Fairness

  Wei Liao, Joel Voldman

• Fed-LSAE: Thwarting Poisoning Attacks against Federated Cyber Threat Detection System via Autoencoder-based Latent Space Inspection

  Tran Duc Luong, Vuong Minh Tien, Nguyen Huu Quyen, Do Thi Thu Hien, Phan The Duy, Van-Hau Pham

2023-09-20

• GPTFUZZER : Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts

  Jiahao Yu, Xingwei Lin, Xinyu Xing

• Exploring the Dark Side of AI: Advanced Phishing Attack Design and Deployment Using ChatGPT

  Nils Begou, Jeremy Vinoy, Andrzej Duda, Maciej Korczynski

• Transferable Adversarial Attack on Image Tampering Localization

  Yuqi Wang, Gang Cao, Zijie Lou, Haochen Zhu

• RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic Segmentation

  Chang Liu, Giulia Rizzoli, Francesco Barbato, Umberto Michieli, Yi Niu, Pietro Zanuttigh

• Realistic Website Fingerprinting By Augmenting Network Trace

  Alireza Bahramali, Ardavan Bozorgi, Amir Houmansadr

• Love or Hate? Share or Split? Privacy-Preserving Training Using Split Learning and Homomorphic Encryption

  Tanveer Khan, Khoa Nguyen, Antonis Michalas, Alexandros Bakas

• Disentangled Information Bottleneck guided Privacy-Protective JSCC for Image Transmission

  Lunan Sun, Yang Yang, Mingzhe Chen, Caili Guo

• SPFL: A Self-purified Federated Learning Method Against Poisoning Attacks

  Zizhen Liu, Weiyang He, Chip-Hong Chang, Jing Ye, Huawei Li, Xiaowei Li

2023-09-19

• Plug in the Safety Chip: Enforcing Constraints for LLM-driven Robot Agents

  Ziyi Yang, Shreyas S. Raman, Ankit Shah, Stefanie Tellex

• Efficient Avoidance of Vulnerabilities in Auto-completed Smart Contract Code Using Vulnerability-constrained Decoding

  André Storhaug, Jingyue Li, Tianyuan Hu

• Bias of AI-Generated Content: An Examination of News Produced by Large Language Models

  Xiao Fang, Shangkun Che, Minjia Mao, Hongzhe Zhang, Ming Zhao, Xiaohang Zhao

• Reducing Adversarial Training Cost with Gradient Approximation

  Huihui Gong, Shuo Yang, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu

• Stealthy Physical Masked Face Recognition Attack via Adversarial Style Optimization

  Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu

• Evaluating Adversarial Robustness with Expected Viable Performance

  Ryan McCoppin, Colin Dawson, Sean M. Kennedy, Leslie M. Blaha

2023-09-17

• Convex Latent-Optimized Adversarial Regularizers for Imaging Inverse Problems

  Huayu Wang, Chen Luo, Taofeng Xie, Qiyu Jin, Guoqing Chen, Zhuo-Xu Cui, Dong Liang

2023-09-16

• Robust Backdoor Attacks on Object Detection in Real World

  Yaguan Qian, Boyuan Ji, Shuke He, Shenhui Huang, Xiang Ling, Bin Wang, Wei Wang

• Investigating Subtler Biases in LLMs: Ageism, Beauty, Institutional, and Nationality Bias in Generative Models

  Mahammed Kamruzzaman, Md. Minul Islam Shovon, Gene Louis Kim

• Context-aware Adversarial Attack on Named Entity Recognition

  Shuguang Chen, Leonardo Neves, Thamar Solorio

2023-09-15

• Adversarial Attacks on Tables with Entity Swap

  Aneta Koleva, Martin Ringsquandl, Volker Tresp

• A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning

  Tanveer Khan, Khoa Nguyen, Antonis Michalas

• Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection

  Yasir Ali Farrukh, Syed Wali, Irfan Khan, Nathaniel D. Bastian

• Detecting ChatGPT: A Survey of the State of Detecting ChatGPT-Generated Text

  Mahdi Dhaini, Wessel Poelman, Ege Erdogan

• Keep your Identity Small: Privacy-preserving Client-side Fingerprinting

  Alberto Fernandez-de-Retana, Igor Santos-Grueiro

• Fake News Detectors are Biased against Texts Generated by Large Language Models

  Jinyan Su, Terry Yue Zhuo, Jonibek Mansurov, Di Wang, Preslav Nakov