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
2021
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
2020
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
2019
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
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
2016
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
Defense
2021
Graph Embedding for Recommendation against Attribute Inference Attacks, WWW, 📝Paper
Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality, Arxiv, 📝Paper
2020
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
2019
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
2018
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
2017
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
2016
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
Survey
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