个性化推荐攻击检测模型研究  

Research about personalized recommendation attack detect models

作　　者：董斯维[1] 郭斌[1] 余力[1] 

机构地区：[1]中国人民大学信息学院,北京100872

出　　处：《农业网络信息》2006年第12期111-112,共2页Agriculture Network Information

摘　　要：协同过滤是最核心、最典型的个性化推荐技术,广泛应用于电子商务,但其推荐结果对用户偏好信息的敏感性使得推荐系统易受到人为攻击,电子商务推荐安全成为个性化推荐能否成功应用的关键。作者先简要介绍了个性化推荐及推荐攻击的基本概念;而后分析比较了各种攻击检测模型。Collaborative filtering which is used widely is vital central technology of personalized recommendation,but the recommended result is so sensitive to user perfect information that the recommended system has significant vulnerabilities. E-business recommended secure is the key of whether the personalized recommendation can success. Concepts of the personalized recommend system and recommended attacks were introduced first. Then the author analyzed analysis and compared the attack detect models.

关 键 词：协同过滤 个性化推荐 攻击检测模型 电子商务安全 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]