关键词: 协同推荐系统, 统计过程控制, 用户概貌项目评价数偏离度, 托攻击, 攻击检测

Abstract: Because of the open nature of collaborative recommender systems and their reliance on user-specified judgments for building profiles, an attacker could affect the prediction by injecting a lot of biased data. In order to keep the authenticity of recommendations, the attack detection method based on Statistical Process Control (SPC) was proposed. The method constructed the Shewhart control chart by using the users' deviation from the average of rating numbers and detected attackers according to the warning rules of the chart, thus improving the robustness of collaborative recommender systems. The experiments demonstrate that the method is effective with high precision and high recall against a variety of attack models.

Key words: collaborative recommender system, Statistical Process Control (SPC), deviation from average of rating number, shilling attack, attack detection