一种改进的系统间隐私保持协同过滤推荐算法  

Improved privacy-preserving collaborative filtering recommendation algorithm between systems

作　　者：吴涛[1] 黄莉静[2] 

机构地区：[1]河北联合大学现代技术教育中心,河北唐山063009 [2]河北科技大学信息科学与工程学院,石家庄050018

出　　处：《计算机工程与应用》2013年第15期80-83,122,共5页Computer Engineering and Applications

基　　金：河北省自然科学基金(No.F2008000115;No.F2012208004)

摘　　要：针对系统间协同过滤推荐过程中的隐私泄露问题,以RSA公钥密码系统和安全多方计算SMC理论为基础,提出一个安全计算模型SCM,将安全计算模型SCM应用到系统间协同过滤中,得到一个有效的隐私保持协同过滤推荐算法。算法利用安全矢量积计算用户的相似度,防止了第三方的恶意串通。实验表明,该算法不但可以保护用户的隐私不泄露给协同合作的系统,而且提高了推荐算法的精度,特别是对用户数据稀疏的小站点。To solve the privacy disclosure problem of the recommendation algorithm between systems, this paper addresses a secure computation model based on RSA public key cryptosystem and secure multi-party computation. Applying this model to the collaborative filtering between systems, an efficient privacy-preserving collaborative filtering recommender algorithm is pro-posed. The algorithm uses secure vector product to calculate the similarity of users, prevents the untrusted third party from col- luding. Experimental results show that algorithm not only has stronger ability to protect the user＇ s privacy disclosing to the sys-tem which is cooperated, but also has better quality of recommendation, especially for the small system of sparse data.

关 键 词：协同过滤 隐私保持 安全多方计算 RSA公钥密码 安全计算模型 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]