An Effective Recommender Attack Detection Method based on Time SFM Factors

摘要：

Users Preference information has significant impact on the recommendations. It makes recommender system vulnerable. To make detection and discrimination of attack users accurate and recommendations objective, time intervals of users rates was taken into consideration. After a series of Rate-time pretreatment, SFM factors short for span, frequency and Mount properties were summed up, representing time attributes of user behaviors. An effective attack detection method based on time SFM factors is proposed to more effectively prevent their interferences with TopN recommendation lists for users. Experiment results support the conclusion.

关键词： Recommender attack Attack model Attack detection Time SFM Factors

作者: Tong Tang Yan Tang

作者单位: College of Mathematics and Statistics Southwest University Chongqing, 400715, China College of Computer and Information Science Southwest University Chongqing, 400715, China

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Information and Education Technology(ICIET 2011)(2011年信息和教育技术国际会议)

会议地点: 贵阳

会议语种:英文

页码: 78-81

在线出版日期: 2011-01-26（万方平台首次上网日期，不代表论文的发表时间）