- PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion, WSDM, 📝Paper
- Targeted Data Poisoning Attack on News Recommendation System， Arxiv, 📝Paper
- FedRecAttack: Model Poisoning Attack to Federated Recommendation, ICDE, 📝Paper,
Code - Poisoning Deep Learning based Recommender Model in Federated Learning Scenarios, IJCAI, 📝Paper
- A Black-Box Attack Model for Visually-Aware Recommender Systems, WSDM, 📝Paper
- Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack, Information Sciences, 📝Paper
- Data Poisoning Attack against Recommender System Using Incomplete and Perturbed Data, KDD, 📝Paper
- Triple Adversarial Learning for Influence based Poisoning Attack in Recommender Systems, KDD, 📝Paper
- Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction, RecSys, 📝Paper
- Membership Inference Attacks Against Recommender Systems, Arxiv, 📝Paper
- Data Poisoning Attacks on Neighborhood-based Recommender Systems, ETT, 📝Paper
- Attacking Black-box Recommendations via Copying Cross-domain User Profiles, Arxiv, 📝Paper
- Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems, SIGIR, 📝Paper
- Adversarial Attacks on Linear Contextual Bandits, Arxiv, 📝Paper
- Adversarial Item Promotion: Vulnerabilities at the Core of Top-N Recommenders that Use Images to Address Cold Start, Arxiv, 📝Paper, Code
- Influence Function based Data Poisoning Attacks to Top-N Recommender Systems, WWW, 📝Paper
- TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems, Dependable and Secure Machine Learning (DSML), 📝Paper, Code
- Adversarial Attacks on Time Series, IEEE Transactions on Pattern Analysis and Machine Intelligence, 📝Paper
- Attacking Recommender Systems with Augmented User Profiles, Arxiv, 📝Paper
- Practical Data Poisoning Attack against Next-Item Recommendation, WWW, 📝Paper
- PoisonRec: An Adaptive Data Poisoning Framework for Attacking Black-box Recommender Systems, ICDE, 📝Paper
- Data Poisoning Attacks against Differentially Private Recommender Systems, SIGIR, 📝Paper
- Revisiting Adversarially Learned Injection Attacks Against Recommender Systems, RecSys, 📝Paper
- Adversarial Attacks on an Oblivious Recommender, RecSys, 📝Paper
- Targeted Poisoning Attacks on Social Recommender Systems, IEEE Global Communications Conference (GLOBECOM), 📝Paper
- Data Poisoning Attacks on Graph Convolutional Matrix Completion，International Conference on Algorithms and Architectures for Parallel Processing, 📝Paper
- Data Poisoning Attacks on Stochastic Bandits, ICML, 📝Paper
- Data Poisoning Attacks on Cross-domain Recommendation, CIKM, 📝Paper
- Assessing the Impact of a User-Item Collaborative Attack on Class of Users, RecSys Workshop, 📝Paper
- Poisoning attacks to graph-based recommender systems, Annual Computer Security Applications Conference (ACSAC), 📝Paper, Code
- Fake Co-visitation Injection Attacks to Recommender Systems, NDSS, 📝Paper
- Hybrid attacks on model-based social recommender systems, Physica A: Statistical Mechanics and its Applications, 📝Paper
- Data Poisoning Attacks on Factorization-Based Collaborative Filtering, NIPS, 📝Paper, Code
- Segment-Focused Shilling Attacks against Recommendation Algorithms in Binary Ratings-based Recommender Systems, International Journal of Hybrid Information Technology, 📝Paper
- Shilling attack models in recommender system, International Conference on Inventive Computation Technologies (ICICT), 📝Paper
- Graph Embedding for Recommendation against Attribute Inference Attacks, WWW, 📝Paper
- Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality, Arxiv, 📝Paper
- GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection, Arxiv, 📝Paper
- On Detecting Data Pollution Attacks On Recommender Systems Using Sequential GANs, ICML, 📝Paper
- A Robust Hierarchical Graph Convolutional Network Model for Collaborative Filtering, Arxiv, 📝Paper
- Adversarial Collaborative Auto-encoder for Top-N Recommendation, Arxiv, 📝Paper
- Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems, Arxiv, 📝Paper
- Adversarial Learning to Compare: Self-Attentive Prospective Customer Recommendation in Location based Social Networks, WSDM, 📝Paper
- Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines, SIGIR, 📝Paper
- Directional Adversarial Training for Recommender Systems, ECAI, 📝Paper
- Shilling Attack Detection Scheme in Collaborative Filtering Recommendation System Based on Recurrent Neural Network, Future of Information and Communication Conference, 📝Paper
- Learning Product Rankings Robust to Fake Users， Arxiv, 📝Paper
- Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning, WSDM, 📝Paper
- Quick and accurate attack detection in recommender systems through user attributes, RecSys, 📝Paper
- Global and Local Differential Privacy for Collaborative Bandits, RecSys, 📝Paper
- Towards Safety and Sustainability: Designing Local Recommendations for Post-pandemic World, RecSys, 📝Paper
- GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection, RecSys, 📝Paper
- Adversarial Training Towards Robust Multimedia Recommender System, TKDE, 📝Paper, Code
- Adversarial Collaborative Neural Network for Robust Recommendation, SIGIR, 📝Paper
- Adversarial Mahalanobis Distance-based Attentive Song Recommender for Automatic Playlist Continuation, SIGIR, 📝Paper, Code
- Adversarial tensor factorization for context-aware recommendation, RecSys, 📝Paper, [:octocat:Code]
- Adversarial Training-Based Mean Bayesian Personalized Ranking for Recommender System, IEEE Access, 📝Paper
- Securing the Deep Fraud Detector in Large-Scale E-Commerce Platform via Adversarial Machine Learning Approach，WWW, 📝Paper
- Shilling Attack Detection in Recommender System Using PCA and SVM, Emerging technologies in data mining and information security, 📝Paper
- Adversarial Personalized Ranking for Recommendation, SIGIR, 📝Paper, Code
- A shilling attack detector based on convolutional neural network for collaborative recommender system in social aware network, The Computer Journal, 📝Paper
- Adversarial Sampling and Training for Semi-Supervised Information Retrieval, WWW, 📝Paper
- Enhancing the Robustness of Neural Collaborative Filtering Systems Under Malicious Attacks, IEEE Transactions on Multimedia, 📝Paper
- An Obfuscated Attack Detection Approach for Collaborative Recommender Systems, Journal of computing and information technology, 📝Paper
- Detecting Abnormal Profiles in Collaborative Filtering Recommender Systems, Journal of Intelligent Information Systems, 📝Paper
- Detection of Profile Injection Attacks in Social Recommender Systems Using Outlier Analysis, IEEE Big Data, 📝Paper
- Prevention of shilling attack in recommender systems using discrete wavelet transform and support vector machine, Eighth International Conference on Advanced Computing (ICoAC), 📝Paper
- Discovering shilling groups in a real e-commerce platform, Online Information Review, 📝Paper
- Shilling attack detection in collaborative filtering recommender system by PCA detection and perturbation, International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), 📝Paper
- Re-scale AdaBoost for attack detection in collaborative filtering recommender systems, KBS, 📝Paper
- SVM-TIA a shilling attack detection method based on SVM and target item analysis in recommender systems, Neurocomputing, 📝Paper
- A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks, ACM Computing Surveys (CSUR) 2021, 📝Paper
- Adversarial Machine Learning in Recommender Systems: State of the art and Challenges, Arxiv2020, 📝Paper
- A Survey of Adversarial Learning on Graphs, Arxiv2020, 📝Paper
- Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study, Arxiv2020, 📝Paper
- Shilling attacks against collaborative recommender systems: a review, Artificial Intelligence Review, 📝Paper
- Adversarial Attacks and Defenses in Images, Graphs and Text: A Review, Arxiv2019, 📝Paper
- A Survey of Attacks in Collaborative Recommender Systems, Journal of Computational and Theoretical Nanoscience 2019, 📝Paper
- Adversarial Attack and Defense on Graph Data: A Survey, Arxiv2018, 📝Paper
- Adversarial Machine Learning: The Case of Recommendation Systems, IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 📝Paper
- Recommender Systems: Attack Types and Strategies, AAAI2005, 📝Paper
- A Review of Attacks and Its Detection Attributes on Collaborative Recommender Systems, IJARCS2017, 📝Paper
- Awesome Graph Adversarial Learning Link
- Awesome Graph Attack and Defense Papers Link
- Graph Adversarial Learning Literature Link
- A Complete List of All (arXiv) Adversarial Example Papers 🌐Link
- Robust Matrix Completion via Robust Gradient Descent 🌐Link
- **Adversarial Machine Learning in Recommender Systems:Literature Review and Future Visions ** Link