Recommender Systems and Security Issues
|Location:||1131 Kemper Hall|
|When:||Thu May 08, 2008 15:10|
Recommender systems have helped to address the "information overload" problem by sifting through huge amount of information. Because a recommender system is fully dependent on information from users, it might be manipulated by some adversaries. Malicious attacks might make specific items appear more or less popular than they truly are. This talk will first give an overview of recommender systems and introduce the attack models. Then, a series of approaches to detect a diverse and general set of recommendation attacks will be presented. Finally, the future work, such as potential new attack models, will be discussed.
Short Bio: Zhengyi Le received her Ph.D. majored in Computer Science at Dartmouth College. Previously, she received her BS degree in computer science from Nanjing University, China. She is now a Postdoc and the assistant director of Heracleia Lab in University of Texas at Arlington.