A curated list of AI Security & Privacy academic events

Seminar

• NLP & LLM Security
• Privacy and Security in ML (PriSec-ML)
• Machine Learning Security (MLSec)
• Seminars on Security & Privacy in Machine Learning (ML S&P)
• AI Security and Privacy (AISP) (in Chinese)

Conference

• IEEE Conference on Secure and Trustworthy Machine Learning (2022-)
• The Conference on Applied Machine Learning in Information Security (2017-)

Workshop

• Security & Privacy

  • Artificial Intelligence and Security (CCS 2008-)
  • Deep Learning Security and Privacy (S&P 2018-)
  • Dependable and Secure Machine Learning (DSN 2018-)
  • Security Architectures for Generative-AI Systems (S&P 2024)
  • AI System with Confidential Computing (NDSS 2024)

• Machine Learning & Artificial Intelligence

  • Secure and Trustworthy Large Language Models (ICLR 2024)
  • Reliable and Responsible Foundation Models (ICLR 2024)
  • Privacy Regulation and Protection in Machine Learning (ICLR 2024)
  • Responsible Language Models (AAAI 2024)
  • Privacy-Preserving Artificial Intelligence (AAAI 2020-2024)
  • Practical Deep Learning in the Wild (CAI 2024, AAAI 2022-2023)
  • Backdoors in Deep Learning: The Good, the Bad, and the Ugly (NeurIPS 2023)
  • Trustworthy and Reliable Large-Scale Machine Learning Models (ICLR 2023)
  • Backdoor Attacks and Defenses in Machine Learning (ICLR 2023)
  • Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (ICLR 2022)
  • Security and Safety in Machine Learning Systems (ICLR 2021)
  • Robust and Reliable Machine Learning in the Real World (ICLR 2021)
  • Towards Trustworthy ML: Rethinking Security and Privacy for ML (ICLR 2020)
  • Safe Machine Learning: Specification, Robustness and Assurance (ICLR 2019)
  • New Frontiers in Adversarial Machine Learning (ICML 2022-2023)
  • Theory and Practice of Differential Privacy (ICML 2021-2022)
  • Uncertainty & Robustness in Deep Learning (ICML 2020-2021)
  • A Blessing in Disguise: The Prospects and Perils of Adversarial Machine Learning (ICML 2021)
  • Security and Privacy of Machine Learning (ICML 2019)
  • Socially Responsible Machine Learning (NeurIPS 2022, ICLR 2022, ICML 2021)
  • ML Safety (NeurIPS 2022)
  • Privacy in Machine Learning (NeurIPS 2021)
  • Dataset Curation and Security (NeurIPS 2020)
  • Security in Machine Learning (NeurIPS 2018)
  • Machine Learning and Computer Security (NeurIPS 2017)
  • Adversarial Training (NeurIPS 2016)
  • Reliable Machine Learning in the Wild (NeurIPS 2016)
  • Adversarial Learning Methods for Machine Learning and Data Mining (KDD 2019-2022)
  • Privacy Preserving Machine Learning (FOCS 2022, CCS 2021, NeurIPS 2020, CCS 2019, NeurIPS 2018)
  • SafeAI (AAAI 2019-2022)
  • Adversarial Machine Learning and Beyond (AAAI 2022)
  • Towards Robust, Secure and Efficient Machine Learning (AAAI2021)
  • AISafety (IJCAI 2019-2022)

• Computer Vision

  • Adversarial Machine Learning on Computer Vision (CVPR 2024, CVPR 2023, CVPR 2022, CVPR 2020)
  • Secure and Safe Autonomous Driving (CVPR 2023)
  • Adversarial Robustness in the Real World (ICCV 2023, ECCV 2022, ICCV 2021, CVPR 2021, ECCV 2020, CVPR 2020, CVPR 2019)
  • The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CVPR 2021, ECCV 2020, CVPR 2019, CVPR 2018, CVPR 2017)
  • Responsible Computer Vision (ECCV 2022)
  • Safe Artificial Intelligence for Automated Driving (ECCV 2022)
  • Adversarial Learning for Multimedia (ACMMM 2021)
  • Adversarial Machine Learning towards Advanced Vision Systems (ACCV 2022)

• Natural Language Processing

  • BlackboxNLP (EMNLP 2022, EMNLP 2021, EMNLP 2020, ACL 2019, EMNLP 2018)

• Information Retrieval

  • Online Misinformation- and Harm-Aware Recommender Systems (RecSys 2021, RecSys 2020)
  • Adversarial Machine Learning for Recommendation and Search (CIKM 2021)

Tutorial

• Machine Learning & Artificial Intelligence

  • Quantitative Reasoning About Data Privacy in Machine Learning (ICML 2022)
  • Foundational Robustness of Foundation Models (NeurIPS 2022)
  • Adversarial Robustness - Theory and Practice (NeurIPS 2018)
  • Towards Adversarial Learning: from Evasion Attacks to Poisoning Attacks (KDD 2022)
  • Adversarial Robustness in Deep Learning: From Practices to Theories (KDD 2021)
  • Adversarial Attacks and Defenses: Frontiers, Advances and Practice (KDD 2020)
  • Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications (ICDM 2020)
  • Adversarial Machine Learning for Good (AAAI 2022)
  • Adversarial Machine Learning (AAAI 2018)

• Computer Vision

  • Adversarial Machine Learning in Computer Vision (CVPR 2021)
  • Practical Adversarial Robustness in Deep Learning: Problems and Solutions (CVPR 2021)
  • Adversarial Robustness of Deep Learning Models (ECCV 2020)
  • Deep Learning for Privacy in Multimedia (ACMMM 2020)

• Natural Language Processing

  • Vulnerabilities of Large Language Models to Adversarial Attacks (ACL 2024)
  • Robustness and Adversarial Examples in Natural Language Processing (EMNLP 2021)
  • Deep Adversarial Learning for NLP (NAACL 2019)

• Information Retrieval

  • Adversarial Machine Learning in Recommender Systems (ECIR 2021, RecSys 2020, WSDM 2020)

Special Session

• Special Track on Safe and Robust AI (AAAI 2023)
• Special Session on Adversarial Learning for Multimedia Understanding and Retrieval (ICMR 2022)
• Special Session on Adversarial Attack and Defense (APSIPA 2022)
• Special Session on Information Security meets Adversarial Examples (WIFS 2019)