Personalized recommendation systems can help users to get the information thai they really want,but good recommendation depends on a great deal of information about users. Those information maybe arouse the users' concern about their privacy which lead to lose the users' trust in recommendation systems, so a lot of study focused on the privacy protection techniques. These techniques can protect users privacy, at the same time, recommendation systems can get good recommendations. This paper mainly discussed privacy protection techniques applied in personalized recommendation systems, and gave the definition of privacy and privacy protection. It discussed some privacy protection techniques including privacy policy languages and privacy protection techniques used at present. At last it summaried the key points and directions of this study in the future.%个性化推荐系统能较好地帮助用户获得个人所需的信息,但它要获得好的推荐效果,需要收集大量的用户个人信息；这些信息可能泄露个人隐私,用户会因对隐私泄露的担心而放弃对推荐系统的信任,所以大量的研究集中于如何在获得高效推荐的同时保护用户的个人隐私.主要就个性化推荐系统中使用的隐私保护技术进行了综述,在给出了隐私和隐私保护定义的同时讨论了隐私保护的相关技术,包括隐私策略描述语言和目前使用的隐私保护技术.最后尝试给出了今后的研究重点和方向.
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