sisinflab / adversarial-recommender-systems-survey

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-dimensional) data distributions. In this survey, we provide an exhaustive literature review of 74 articles published in major RS and ML journals and conferences. This review serves as a reference for the RS community, working on the security of RS or on generative models using GANs to improve their quality.

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:

• Felice Antonio Merra [e-mail]
• Yashar Deldjoo [e-mail]
• Tommaso Di Noia [e-mail]