GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Promoting Recommendations: An Attack on Collaborative Filtering
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Collaborative Filtering with Privacy
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Shilling recommender systems for fun and profit
Proceedings of the 13th international conference on World Wide Web
PocketLens: Toward a personal recommender system
ACM Transactions on Information Systems (TOIS)
Collaborative recommendation: A robustness analysis
ACM Transactions on Internet Technology (TOIT)
A clickstream-based collaborative filtering personalization model: towards a better performance
Proceedings of the 6th annual ACM international workshop on Web information and data management
User evaluation of the NASA technical report server recommendation service
Proceedings of the 6th annual ACM international workshop on Web information and data management
Finding group shilling in recommendation system
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
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
Lies and propaganda: detecting spam users in collaborative filtering
Proceedings of the 12th international conference on Intelligent user interfaces
Attacks and Remedies in Collaborative Recommendation
IEEE Intelligent Systems
Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness
ACM Transactions on Internet Technology (TOIT)
The influence limiter: provably manipulation-resistant recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
Robust collaborative filtering
Proceedings of the 2007 ACM conference on Recommender systems
Attack resistant collaborative filtering
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
The information cost of manipulation-resistance in recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Unsupervised retrieval of attack profiles in collaborative recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Collaborative web search: a robustness analysis
Artificial Intelligence Review
Manipulation-resistant recommender systems through influence limits
ACM SIGecom Exchanges
Trustworthy knowledge diffusion model based on risk discovery on peer-to-peer networks
Expert Systems with Applications: An International Journal
Unsupervised strategies for shilling detection and robust collaborative filtering
User Modeling and User-Adapted Interaction
Effective diverse and obfuscated attacks on model-based recommender systems
Proceedings of the third ACM conference on 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
Dependable filtering: Philosophy and realizations
ACM Transactions on Information Systems (TOIS)
Reliable medical recommendation systems with patient privacy
Proceedings of the 1st ACM International Health Informatics Symposium
Social manipulation of online recommender systems
SocInfo'10 Proceedings of the Second international conference on Social informatics
Analysis and detection of segment-focused attacks against collaborative recommendation
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
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
A hybrid decision approach to detect profile injection attacks in collaborative recommender systems
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
Knowledge-Based Systems
βP: A novel approach to filter out malicious rating profiles from recommender systems
Decision Support Systems
Iolaus: securing online content rating systems
Proceedings of the 22nd international conference on World Wide Web
A belief propagation approach for detecting shilling attacks in collaborative filtering
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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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Collaborative filtering techniques have been successfully employed in recommender systems in order to help users deal with information overload by making high quality personalized recommendations. However, such systems have been shown to be vulnerable to attacks in which malicious users with carefully chosen profiles are inserted into the system in order to push the predictions of some targeted items. In this paper we propose several metrics for analyzing rating patterns of malicious users and evaluate their potential for detecting such shilling attacks. Building upon these results, we propose and evaluate an algorithm for protecting recommender systems against shilling attacks. The algorithm can be employed for monitoring user ratings and removing shilling attacker profiles from the process of computing recommendations, thus maintaining the high quality of the recommendations.