Computer Science and Application 计算机科学与应用, 2016, 6(7), 451-458 Published Online July 2016 in Hans. http://www.hanspub.org/journal/csa http://dx.doi.org/10.12677/csa.2016.67055 文章引用: 李晨晨, 张乐峰, 惠慧, 熊平. 一种基于隐私保护的协同过滤推荐算法[J]. 计算机科学与应用, 2016, 6(7): 451-458. http://dx.doi.org/10.12677/csa.2016.67055 A Collaborative Filtering Recommender Algorithm Based on Privacy Preserving Chenchen Li, Lefeng Zhang, Hui Hui, Ping Xiong School of Information and Security Engineering, Zhongnan University of Economics and Law, Wuhan Hubei Received: Jul. 7 th , 2016; accepted: Jul. 26 th , 2016; published: Jul. 29 th , 2016 Copyright © 2016 by authors and Hans Publishers Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract Privacy preserving in recommender system is a hot research area currently. With the premise that recommender system server is untrusted, we propose a privacy-preserving collaborative filtering algorithm based on substitution encryption. Users encrypt their rating information at the client side and submit it to the recommender server. With the encrypted ratings collected from users, the recommender server predicts the ratings for users on unrated items with collaborative filter- ing algorithm. We represent a method for computing the similarity of users without knowing the meaning of the ratings, which is used for identifying the nearest neighbors of each user in colla- borative filtering and predicting. The experimental results demonstrate the superiority of the proposed method comparing to the traditional collaborative filtering recommender algorithms. Keywords Privacy Preserving, Collaborative Filtering, Recommender System, Substitution Encryption 一种基于隐私保护的协同过滤推荐算法 李晨晨，张乐峰，惠 慧，熊 平 中南财经政法大学信息与安全工程学院，湖北 武 收稿日期：2016年7月7日；录用日期：2016年7月26日；发布日期：2016年7月29日