华东师范大学学报（自然科学版）Issue(2)：41-51,62,12.DOI:10.3969/j.issn.1000-5641.2018.02.005
高效可验证的隐私保护推荐系统
Efficient verifiable privacy-preserving recommendation system
摘要
Abstract
To address the problem of privacy disclosure in traditional personalized recommendation systems,this paper proposes an efficient verifiable privacy-preserving recommendation system,which can provide user the way to verify the correctness of the resulting model of cloud computing under the premise of protecting user's data privacy.This paper uses ridge regression to find the best-fit linear curve of user's input data,and implements Yao's garbled circuit to realize the computation and the correctness verification of the recommendation model.The user and the cloud use a newly-devised privacy preserving data aggregation method named AGG (Aggregation) to replace public key homomorphic encryption used in most existing work,which can reduce the computational overhead of the user and the cloud,thus making the system more efficient.The security analysis and the efficiency analysis of the scheme are given at the end of the article.关键词
个性化推荐系统/脊回归/隐私保护/混淆电路/可验证计算Key words
personalized recommendation system/ridge regression/privacy preservation/garbled circuits/verifiable computation分类
信息技术与安全科学引用本文复制引用
宋春芝,董晓蕾,曹珍富..高效可验证的隐私保护推荐系统[J].华东师范大学学报（自然科学版）,2018,(2):41-51,62,12.基金项目
国家自然科学基金(61602180,61632012,61672239) （61602180,61632012,61672239）
上海市自然科学基金(16ZR1409200) （16ZR1409200）
上海市高新技术领域项目(16511101400) （16511101400）
