GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Shilling recommender systems for fun and profit
Proceedings of the 13th international conference on World Wide Web
Utility-based neighbourhood formation for efficient and robust collaborative filtering
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Collaborative recommendation: A robustness analysis
ACM Transactions on Internet Technology (TOIT)
Finding group shilling in recommendation system
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Preventing shilling attacks in online recommender systems
Proceedings of the 7th annual ACM international workshop on Web information and data management
Classification features for attack detection in collaborative recommender systems
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Attack detection in time series for recommender systems
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness
ACM Transactions on Internet Technology (TOIT)
Effective diverse and obfuscated attacks on model-based recommender systems
Proceedings of the third ACM conference on Recommender systems
Detecting profile injection attacks in collaborative filtering: a classification-based approach
WebKDD'06 Proceedings of the 8th Knowledge discovery on the web international conference on Advances in web mining and web usage analysis
On the stability of recommendation algorithms
Proceedings of the fourth ACM conference on Recommender systems
Semi-SAD: applying semi-supervised learning to shilling attack detection
Proceedings of the fifth ACM conference on Recommender systems
Guest editorial: special issue on a decade of mining the Web
Data Mining and Knowledge Discovery
HySAD: a semi-supervised hybrid shilling attack detector for trustworthy product recommendation
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Stability of Recommendation Algorithms
ACM Transactions on Information Systems (TOIS)
Reliable medical recommendation systems with patient privacy
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Defending recommender systems by influence analysis
Information Retrieval
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Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. These vulnerabilities mostly emanate from the open nature of such systems and their reliance on user-specified judgments for building profiles. Attackers can easily introduce biased data in an attempt to force the system to “adapt” in a manner advantageous to them. Our research in secure personalization is examining a range of attack models, from the simple to the complex, and a variety of recommendation techniques. In this chapter, we explore an attack model that focuses on a subset of users with similar tastes and show that such an attack can be highly successful against both user-based and item-based collaborative filtering. We also introduce a detection model that can significantly decrease the impact of this attack.