基于安全多方计算的系统间隐私保持推荐算法  

Inter-systems privacy-preserving recommendation algorithm based on security multi-party computation

作　　者：张明磊 韩明[2] 王震洲[3] 

机构地区：[1]河北科技大学党政办公室,河北石家庄050018 [2]燕山大学信息科学与工程学院,河北秦皇岛066004 [3]河北科技大学信息科学与工程学院,河北石家庄050018

出　　处：《河北工业大学学报》2012年第4期14-18,共5页Journal of Hebei University of Technology

基　　金：河北省自然科学基金(F2008000115)

摘　　要：针对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理论为基础,提出一个安全计算模型,并将此模型应用到跨系统协同过滤中,并提出一个基于安全计算模型的跨系统隐私保持协同过滤推荐算法.该算法可有效防止不可信第三方和系统间恶意串通.实验表明,与传统的单系统协同过滤推荐算法相比,该算法不但可以保护用户对项目的评分,并且提高了协同过滤推荐算法的精度.To solve the privacy disclosure problem of the recommendation algorithm,we 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 proposed in this paper.The algorithm using secure vector product to calculates the similarity of users,preventing the untrusted third party colluded.Experimental results show that algorithm not only have stronger ability to protect the user's privacy disclosing to the system which is cooperated,but also has better quality of recommendation.

关 键 词：协同过滤 隐私保持 安全多方计算 RSA 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]