Analysis of Love-hate Shilling Attack against E-commerce Recommender System

摘要：

Recent research has focus on examining the security of e-commerce collaborative filtering(CF) recommender system. Love/hate attack is one of the most effective model as a nuke attack against the classic user-based CF. In this paper, we examine the effectiveness of Love/hate attack against our topic-level trust based recommendation algorithm that incorporate topic-level trust model into traditional collaborative filtering algorithm. The results of our experiments conducted on well-known dataset show that Love/hate attack is more robust against topic-level trust based recommendation algorithm than against classical userbased CF algorithm.

关键词： recommender system love/hate attack collaborative Jittering topic-level trust

作者: Fuguo Zhang

作者单位: School of Information Technology, Jiangxi University of Finance & Economics, Nanchang 330013 China

会议类型: 国际会议

会议名称: 2010 International Conference of Informationa Science and Management Engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

会议地点: 西安

会议语种:英文

页码: 318-321

在线出版日期: 2010-08-07（万方平台首次上网日期，不代表论文的发表时间）