Shilling Attack and Defense on Recommender System (Updating)
- Attacking Click-through Rate Predictors via Generating Realistic Fake Samples, TKDD. 📝Paper
- Uplift Modeling for Target User Attacks on Recommender Systems, arXiv. 📝Paper
- ToDA: Target-oriented Diffusion Attacker against Recommendation System, arXiv. 📝Paper
- Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles, TKDE. 📝Paper
- Influence-Driven Data Poisoning for Robust Recommender Systems, TPAMI. 📝Paper, 📃Code
- Planning Data Poisoning Attacks on Heterogeneous Recommender Systems in a Multiplayer Setting, ICDE. 📝Paper, 📃Code
- Poisoning GNN-based Recommender Systems with Generative Surrogate-based Attacks, TOIS. 📝Paper
- Poisoning Self-supervised Learning Based Sequential Recommendations, SIGIR. 📝Paper, 📃Code
- Practical Cross-System Shilling Attacks with Limited Access to Data, AAAI. 📝Paper, 📃Code
- Revisiting Item Promotion in GNN-Based Collaborative Filtering: A Masked Targeted Topological Attack Perspective, AAAI. 📝Paper
- Shilling Black-box Review-based Recommender Systems through Fake Review Generation, KDD. 📝Paper, 📃Code
- Single-User Injection for Invisible Shilling Attack against Recommender Systems, CIKM. 📝Paper, 📃Code
- Targeted Shilling Attacks on GNN-based Recommender Systems, CIKM. 📝Paper
- The Dark Side of Explanations: Poisoning Recommender Systems with Counterfactual Examples, SIGIR. 📝Paper
- UA-FedRec: Untargeted Attack on Federated News Recommendation, KDD. 📝Paper, 📃Code
- Untargeted Black-box Attacks for Social Recommendations, arXiv. 📝Paper
- Targeted Data Poisoning Attack on News Recommendation System by Content Perturbation, arXiv. 📝Paper
- Poisoning Attacks Against Contrastive Recommender Systems, arXiv. 📝Paper
- Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models, arXiv. 📝Paper
- FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling, KDD. 📝Paper, 📃Code
- Gray-Box Shilling Attack: An Adversarial Learning Approach, TIST. 📝Paper
- Knowledge-enhanced Black-box Attacks for Recommendations, KDD. 📝Paper
- PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion, WSDM. 📝Paper
- Revisiting Injective Attacks on Recommender Systems, NeurIPS. 📝Paper
- Shilling Black-box Recommender Systems by Learning to Generate Fake User Profiles, TNNLS. 📝Paper, 📃Code
- A Black-Box Attack Model for Visually-Aware Recommender Systems, NDSS. 📝Paper, 📃Code
- Attacking Black-box Recommendations via Copying Cross-domain User Profiles, ICDE. 📝Paper
- Attacking Recommender Systems With Plausible Profile, TIFS. 📝Paper
- Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction, RecSys. 📝Paper, 📃Code
- Data Poisoning Attack against Recommender System Using Incomplete and Perturbed Data, KDD. 📝Paper
- Data Poisoning Attacks to Deep Learning Based Recommender Systems, NDSS. 📝Paper
- Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack, Information Sciences. 📝Paper
- Reverse Attack: Black-box Attacks on Collaborative Recommendation, CCS. 📝Paper
- Triple Adversarial Learning for Influence based Poisoning Attack in Recommender Systems, KDD. 📝Paper, 📃Code
- Attacking Recommender Systems with Augmented User Profiles, CIKM. 📝Paper, 📃Code
- How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Modelss, SIGIR. 📝Paper
- Influence Function based Data Poisoning Attacks to Top-N Recommender Systems, WWW. 📝Paper
- PoisonRec: An Adaptive Data Poisoning Framework for Attacking Black-box Recommender Systems, ICDE. 📝Paper
- Practical Data Poisoning Attack against Next-Item Recommendation, WWW. 📝Paper
- Revisiting Adversarially Learned Injection Attacks Against Recommender Systems., RecSys. 📝Paper, 📃Code
- Adversarial Attacks on an Oblivious Recommender, RecSys. 📝Paper
- Data Poisoning Attacks on Cross-domain RecommendationData Poisoning Attacks on Cross-domain Recommendation, CIKM. 📝Paper
- Poisoning Attacks to Graph-Based Recommender Systems, ACSAC. 📝Paper
- Fake Co-visitation Injection Attacks to Recommender Systems, NDSS. 📝Paper
- Data Poisoning Attacks on Factorization-Based Collaborative Filtering, NeurIPS. 📝Paper
- Collaborative Filtering Under a Sybil Attack: Analysis of a Privacy Threat, EuroSec. 📝Paper
- Assessing Impacts of a Power User Attack on a Matrix Factorization Collaborative Recommender System, FLAIRS. 📝Paper
- Attacking Item-Based Recommender Systems with Power Items, RecSys. 📝Paper
- Evil Twins: Modeling Power Users in Attacks on Recommender Systems, UMAP. 📝Paper
- Shilling Attacks against Memory-Based Privacy-Preserving Recommendation Algorithms, TIIS. 📝Paper
- Take This Personally: Pollution Attacks on Personalized Services, USENIX Security Symposium. 📝Paper
- When Power Users Attack: Assessing Impacts in Collaborative Recommender Systems, RecSys. 📝Paper
- Effective Attack Models for Shilling Item-Based Collaborative Filtering System, WEBKDD. 📝Paper
- Limited Knowledge Shilling Attacks in Collaborative Filtering Systems, IJCAI. 📝Paper
- Recommender Systems: Attack Types and Strategies, AAAI. 📝Paper
- Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems, ICDM. 📝Paper
- Shilling Recommender Systems for Fun and Profit, WWW. 📝Paper
- Promoting Recommendations: An Attack on Collaborative Filtering, DEXA. 📝Paper
- Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model, WWW. 📝Paper
- Enhancing Adversarial Robustness of Multi-modal Recommendation via Modality Balancing, MM. 📝Paper
- Influence-Driven Data Poisoning for Robust Recommender Systems, TPAMI. 📝Paper
- On the Vulnerability of Graph Learning-based Collaborative Filtering, TOIS. 📝Paper
- Towards Adversarially Robust Recommendation from Adaptive Fraudster Detection, TIFS. 📝Paper
- PORE: Provably Robust Recommender Systems against Data Poisoning Attacks, arXiv. 📝Paper, 📃Code
- Toward Robust Recommendation via Real-time Vicinal Defense, arXiv. 📝Paper
- Defending Substitution-Based Profile Pollution Attacks on Sequential Recommenders, RecSys. 📝Paper, 📃Code
- Detect Professional Malicious User With Metric Learning in Recommender Systems, TKDE. 📝Paper
- RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems, WSDM. 📝Paper, 📃Code
- Three Birds with One Stone: User Intention Understanding and Influential Neighbor Disclosure for Injection Attack Detection, TIFS. 📝Paper
- Towards Robust Recommender Systems via Triple Cooperative Defense, WISE. 📝Paper, 📃Code
- Fight Fire with Fire: Towards Robust Recommender Systems via Adversarial Poisoning Training, SIGIR. 📝Paper, 📃Code
- Identification of Malicious Injection Attacks in Dense Rating and Co-Visitation Behaviors, TIFS. 📝Paper
- GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection, SIGIR. 📝Paper, 📃Code
- On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs, arXiv. 📝Paper
- Enhancing the Robustness of Neural Collaborative Filtering Systems under Malicious Attacks, TMM. 📝Paper
- Evaluating Recommender System Stability with Influence-Guided Fuzzing, AAAI. 📝Paper
- Quick and Accurate Attack Detection in Recommender Systems through User Attributes, RecSys. 📝Paper
- Unorganized Malicious Attacks Detection, NeurIPS. 📝Paper
- Detecting Abnormal Profiles in Collaborative Filtering Recommender Systems, JIIS. 📝Paper
- Re-Scale Adaboost for Attack Detection in Collaborative Filtering Recommender Systems, KBS. 📝Paper
- Catch the Black Sheep: Unified Framework for Shilling Attack Detection Based on Fraudulent Action Propagation, IJCAI. 📝Paper, 📃Code
- Mitigating Power User Attacks on a User-Based Collaborative Recommender System, FLAIRS. 📝Paper
- Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis, PloS One. 📝Paper
- Defending Recommender Systems by Influence Analysis, Information Retrieval. 📝Paper
- Stability of Matrix Factorization for Collaborative Filtering, ICML. 📝Paper
- Unsupervised Strategies for Shilling Detection and Robust Collaborative Filtering, UMUAI. 📝Paper
- Attack Resistant Collaborative Filtering, SIGIR. 📝Paper
- Unsupervised Retrieval of Attack Profiles in Collaborative Recommender Systems, RecSys. 📝Paper
- Defending Recommender Systems: Detection of Profile Injection Attacks, SOCA. 📝Paper
- Robust Collaborative Filtering, RecSys. 📝Paper
- Robustness of Collaborative Recommendation Based on Association Rule Mining, RecSys. 📝Paper
- The Influence Limiter: Provably Manipulation-Resistant Recommender Systems, RecSys. 📝Paper
- Toward trustworthy recommender systems: An Analysis of Attack Models and Algorithm Robustness, TOIT. 📝Paper
- Unsupervised Shilling Detection for Collaborative Filtering, AAAI. 📝Paper
- Classification Features for Attack Detection in Collaborative Recommender Systems, KDD. 📝Paper
- Detection of Obfuscated Attacks in Collaborative Recommender Systems, ECAI Workshop on Recommender Systems. 📝Paper
- Securing Collaborative Filtering against Malicious Attacks through Anomaly Detection, ITWP. 📝Paper
- The Impact of Attack Profile Classification on the Robustness of Collaborative Recommendation, WEBKDD. 📝Paper
- Analysis and Detection of Segment-Focused Attacks against Collaborative Recommendation, WEBKDD. 📝Paper
- Finding Group Shilling in Recommendation System, WWW. 📝Paper
- Identifying Attack Models for Secure Recommendation, Beyond Personalization IUI. 📝Paper
- Preventing Shilling Attacks in Online Recommender Systems, WIDM. 📝Paper
- Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures, arXiv. 📝Paper
- Poisoning Attacks against Recommender Systems: A Survey, arXiv. 📝Paper
- Towards Robust Recommendation: A Review and an Adversarial Robustness Evaluation Library, arXiv. 📝Paper
- Latest Trends of Security and Privacy in Recommender Systems: A Comprehensive Review and Future Perspectives, Computers & Security. 📝Paper
- A Survey for Trust-Aware Recommender Systems: A Deep Learning Perspective, KBS. 📝Paper
- Trustworthy Recommender Systems, arXiv. 📝Paper
- A Survey on Trustworthy Recommender Systems, arXiv. 📝Paper
- A Comprehensive Survey on Trustworthy Recommender Systems, arXiv. 📝Paper
- A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks, ACM Computing Surveys. 📝Paper
- Shilling Attacks against Collaborative Recommender Systems: A Review, Artificial Intelligence Review. 📝Paper
- Shilling Attacks against Recommender Systems: A Comprehensive Survey, Artificial Intelligence Review. 📝Paper
- A Survey of Attack-Resistant Collaborative Filtering Algorithms, Data Engineering Bulletin Issues. 📝Paper
- A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms, Data Engineering Bulletin Issues. 📝Paper
- Trustworthy Recommender Systems: Foundations and Frontiers, KDD & The Web Conference. 🌐Website
- Trustworthy Recommender Systems: Technical, Ethical, Legal, and Regulatory Perspectives, RecSys. 🌐Website
- Adversarial Machine Learning in Recommender Systems, WSDM & RecSys & ECIR. 🌐Website
- RecAD: Towards A Unified Library for Recommender Attack and Defense, RecSys. 📝Paper, 📃Code
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Paper Reading list for Shilling Attack and Defense on Recommender Systems
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