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“Detecting Profile Injection Attacks in Collaborative Recommender Systems” by Robin Burke, Bamshad Mobasher, Chad Williams, and Runa Bhaumik. In Proceedings of the 8th IEEE Conference on E-Commerce Technology (CEC'06), (San Francisco, California), June 2006.
Collaborative recommender systems are known to be highly vulnerable to profile injection attacks, attacks that involve the insertion of biased profiles into the ratings database for the purpose of altering the system’s recommendation behavior. In prior work, we and others have identified a number of models for such attacks and shown their effectiveness. This paper describes a classification approach to the problem of detecting and responding to profile injection attacks. This technique significantly reduces the effectiveness of the most powerful attack models previously studied.
Keywords: collaborative filtering, recommender systems, recommender robustness, attack detection, profile injection attacks
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BibTeX entry:
@inproceedings{BMWB06b,
author = {Robin Burke and Bamshad Mobasher and Chad Williams and Runa
Bhaumik},
title = {Detecting Profile Injection Attacks in Collaborative
Recommender Systems},
booktitle = {Proceedings of the 8th IEEE Conference on E-Commerce
Technology (CEC'06)},
address = {San Francisco, California},
month = jun,
year = {2006},
url = {http://dx.doi.org/10.1109/CEC-EEE.2006.34}
}