Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. These vulnerabilities mostly emanate from the open nature of such systems ...
Bamshad Mobasher, Robin D. Burke, Chad Williams, R...
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Collaborative filtering (CF) recommender systems are very popular and successful in commercial application fields. However, robustness analysis research has shown that conventional...
Robustness analysis research has shown that conventional memory-based recommender systems are very susceptible to malicious profile-injection attacks. A number of attack models h...
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...