Aug 20, 2006 � We derive a theoretically optimal window size to best detect an attack event if the number of attack profiles is known. For practical�...
We derive a theoretically optimal window size to best detect an attack event if the number of attack proles is known. For practi- cal applications where this�...
Aug 23, 2006 � Recent research has identified significant vulnerabilities in recommender systems. Shilling attacks, in which attackers.
May 9, 2018 � In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed.
Aug 15, 2019 � In this paper, we propose an approach for detecting shilling attacks in social recommender systems based on time series analysis and trust features (TSA–TF).
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Abstract—Recommender systems are widely used in electronic commerce, social media and online streaming services to provide personalized recommendations to�...
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Inproceedings,. Attack detection in time series for recommender systems. S. Zhang, A. Chakrabarti, J. Ford, and F. Makedon. KDD, page 809-814. ACM, (2006 ). 1.
In this paper, we study the use of statistical metrics to detect rating patterns of attackers. Two metrics, Rating Deviation from Mean Agreement (RDMA) and�...
Apr 23, 2024 � This comprehensive survey should serve as a point of reference for protecting recommender systems against poisoning attacks. The article�...
Analysing supervised learning approaches for detecting shilling attacks in collaborative recommendations � Multiview Ensemble Method for Detecting Shilling�...
