Skip to content

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…

master
Switch branches/tags
Code

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time

A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks

A table of adversarial learning publications in recommender systems. This page will be periodically updated to include recent works. Please contact us if your work is not in the list. Let us know if your recent work is not in the list, we will be happy to include it!

The table is complement of the survey below.

A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks

@article{DBLP:journals/corr/abs-2005-10322,
    author = {Yashar Deldjoo and Tommaso {Di Noia} and Felice Antonio Merra},
    title = "A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks",
    journal = "ACM Computing Surveys",
    year = "2021",
    keywords = "Recommender System, Adversarial Machine Learning,
    Literature Review",
    url       = {https://doi.org/10.1145/3439729},
    doi      = {10.1145/3439729}
}

Adversarial Machine Learning in Recommender Systems (AML-RecSys) Tutorial presented at WSDM@2020 slides

@inproceedings{DBLP:conf/wsdm/DeldjooNM20,
  author    = {Yashar Deldjoo and
               Tommaso Di Noia and
               Felice Antonio Merra},
  title     = {Adversarial Machine Learning in Recommender Systems (AML-RecSys)},
  booktitle = {{WSDM} '20: The Thirteenth {ACM} International Conference on Web Search
               and Data Mining, Houston, TX, USA, February 3-7, 2020},
  year      = {2020},
  url       = {https://doi.org/10.1145/3336191.3371877}
  }

Papers

ADVERSARIAL MACHINE LEARNING FOR SECURITY OF RS

Year Title Type Target Model Venue Link Code
2021 Adversarial Item Promotion: Vulnerabilities at the Core of Top-N Recommenders that Use Images to Address Cold Start Attack DVBPR/VBPR/AMR WWW Link Code
2021 A Black-Box Attack Model for Visually-Aware Recommender Systems Attack VBPR/DeepStyle WSDM Link Code
2020 Assessing Perceptual and Recommendation Mutation of Adversarially-Poisoned Visual Recommenders Attack VBPR/AMR NeurIPS-WS Link Code
2020 Attacking Recommender Systems with Augmented User Profiles Attack CF CIKM Link
2020 Multi-Step Adversarial Perturbations on Recommender Systems Embeddings Attack CF arXIv Link Code
2020 Revisiting Adversarially Learned Injection Attacks Against Recommender Systems Attack CF RecSys Link Code
2020 Adversarial Learning for Recommendation: Applications for Security and Generative Tasks — Concept to Code Tutorial BPR-MF RecSys Link Hands-On
2020 TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems Attack VBPR/AMR DSN-DSML Link Code
2020 Adversarial Training-Based Mean Bayesian Personalized Ranking for Recommender System Attack/Defense BPR-MF IEEE Access Link
2020 Adversarial Learning to Compare: Self-Attentive Prospective Customer Recommendation in Location based Social Networks Attack/Defense LBSN WSDM Link
2020 Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning GAN Defense Attribute-Protection WSDM Link
2020 Adversarial Machine Learning in Recommender Systems (AML-RecSys) Tutorial WSDM Link
2019 Adversarial Collaborative Auto-encoder for Top-N Recommendation Attack/Defense CDAE IJCNN Link
2019 Adversarial Collaborative Neural Network for Robust Recommendation Attack/Defense CDAE SIGIR Link
2019 Adversarial Training Towards Robust Multimedia Recommender System Attack/Defense VBPR TKDE Link Code
2019 Enhancing the Robustness of Neural Collaborative Filtering Systems Under Malicious Attacks Attack/Defense NCF IEEE T Mutimedia Link
2019 Adversarial tensor factorization for context-aware recommendation Attack/Defense FM RecSys Link
2019 Adversarial attacks on an oblivious recommender GAN Attacks Linear RecSys Link
2019 Adversarial Sampling and Training for Semi-Supervised Information Retrieval Attack/Defense MF WWW Link
2019 Domain adaptation in display advertising: an application for partner cold-start Defense Adv. Reg. Deep Rec. RecSys Link
2019 Adversarial Mahalanobis Distance-based Attentive Song Recommender for Automatic Playlist Continuation Attack//Defense MDR SIGIR Paper Code
2018 Adversarial Personalized Ranking for Recommendation Attack/Defense BPR-MF SIGIR Link Code

ADVERSARIAL LEARNING FOR GAN-BASED RECOMMENDATION

Year Title Rec. Model Venue Link Code
2020 LARA: Attribute-to-feature Adversarial Learning for New-item Recommendation Hybrid WSDM Link
2019 Collaborative Adversarial Autoencoders: An Effective Collaborative Filtering Model Under the GAN Framework Collaborative IEEE Access Link
2019 Collaborative Generative Adversarial Network for Recommendation Systems Collaborative ICDE Link
2019 Convolutional Adversarial Latent Factor Model for Recommender System Collaborative AAAI Link
2019 PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation Collaborative IJCAI Link
2019 LambdaGAN: Generative Adversarial Nets for Recommendation Task with Lambda Strategy Collaborative IJCNN Link
2019 VAEGAN: A Collaborative Filtering Framework based on Adversarial Variational Autoencoders Collaborative IJCAI Link
2019 RsyGAN: Generative Adversarial Network for Recommender Systems Collaborative IJCNN Link
2019 Adversarial Distillation (Transfer) for Efficient Recommendation with External Knowledge Hybrid TIST Link
2019 Adversarial Training for Review-Based Recommendations SIGIR Link
2019 Enhancing Collaborative Filtering with Generative Augmentation Hybrid KDD Link
2019 APL: Adversarial Pairwise Learning for Recommender Systems Collaborative Expert Syst. Appl. Link Code
2019 Generating Reliable Friends via Adversarial Training to Improve Social Recommendation. Social ICDM Link
2019 Utilizing Generative Adversarial Networks for Recommendation based on Ratings and Reviews Collaborative IJCNN Link
2019 A Minimax Game for Generative and Discriminative Sample Models for Recommendation Hybrid PAKDD Link
2019 Leveraging Long and Short-Term Information in Content-Aware Movie Recommendation via Adversarial Training Time-aware IEEE T CYBERNETICS Link
2019 Generative Adversarial User Model for Reinforcement Learning Based Recommendation System CTR ICML Link Code
2019 Adversarial Point-of-Interest Recommendation. POI WWW Link Code
2019 Deep Adversarial Social Recommendation Social IJCAI Link
2019 Click Feedback-Aware Query Recommendation Using Adversarial Examples Query WWW Link
2019 Scenery-Based Fashion Recommendation with Cross-Domain Geneartive Adverserial Networks Fashion BIGCOMP Link
2019 RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems Fashion IEEE-TNNLS Link
2019 CnGAN: Generative Adversarial Networks for Cross-network user preference generation for non-overlapped users Cross Domain WWW Link Code
2019 C+GAN: Complementary Fashion Item Recommendation Fashion KDD Link
2019 Rating Augmentation with Generative Adversarial Networks towards Accurate Collaborative Filtering Collaborative WWW Link
2019 Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations Privacy ICPRAM Link
2018 CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks Collaborative CIKM Link Code
2018 Adversarial Training of Deep Autoencoders Towards Recommendation Tasks Collaborative IC-NIDC Link
2018 Generative Adversarial Network Based Heterogeneous Bibliographic Net Representation for Personalized Citation Rec Collaborative AAAI Link
2018 GraphGAN: Graph Representation Learning With Generative Adversarial Nets Collaborative AAAI Link Code
2018 A Novel Personalized Citation Recommendation Approach Based on GAN Collaborative ISMIS Link
2018 Leveraging Reconstructive Profiles of Users and Items for Tag-Aware Recommendation Hybrid ICDM Link
2018 Rating Prediction in Review-Based Recommendations via Adversarial Auto-Encoder. Hybrid WI Link
2018 PLASTIC: Prioritize Long and Short-term Information in Top-n Recommendation using Adversarial Training. Sequence-aware IJCAI Link
2018 Using Adversarial Autoencoders for Multi-Modal Automatic Playlist Continuation Sequence-aware RecSys Link Code
2018 Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels. Sequence-aware UMAP Link Code
2018 Neural Memory Streaming Recommender Networks with Adversarial Training. Sequence-aware KDD Link
2018 RecGAN: recurrent generative adversarial networks for recommendation systems Sequence-aware RecSys Link
2018 Compatibility Family Learning for Item Recommendation and Generation Fashion AAAI Link Code
2018 CRAFT: Complementary Recommendation by Adversarial Feature Transform Fashion ECCV Link
2018 An Adversarial Approach to Improve Long-Tail Performance in Neural Collaborative Filtering Collaborative CIKM Link
2017 Augmented variational autoencoders for collaborative filtering with auxiliary information Collaborative CIKM Link
2017 Visually-Aware Fashion Recommendation and Design with Generative Image Models Fashion ICDM Link Code
2017 IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models Collaborative SIGIR Link Code

Authors

This page is managed and maintained by:

About

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…

Topics

Resources

Releases

No releases published

Packages

No packages published