面向推荐系统数据安全的无证书门限解密方案

doi:10.11896/j.issn.1002-137X.2017.11.038

摘要/Abstract

摘要： 推荐系统是解决信息过载问题和满足用户个性化需求的有效途径之一。然而,由于推荐系统需要用户提供不同程度的个性化信息来提升推荐的准确度,因此各种数据的安全问题成为阻碍其发展的重要因素。在基于分布式体系结构的推荐系统中,门限解密技术是抵抗数据安全攻击、保护推荐系统用户隐私的有效方法之一。在无证书公钥密码体制下研究门限解密技术,既避免了传统公钥密码体制中昂贵的证书管理问题,又解决了基于身份密钥体制中固有的密钥托管问题。给出了无证书门限解密系统的形式化定义与安全模型,构建了一个新的无证书门限解密方案,并在随机预言模型下证明了该方案在适应性选择密文攻击下是安全的。与已有的方案相比,该方案的计算代价更小,传输速率更高,主密钥和公钥长度更短,用户之间需要传播的信息量更小。所提方案既能提高推荐系统的信息传输效率,又能有效地保证分布式推荐系统中用户隐私的安全性和可靠性。

关键词: 推荐系统,数据安全,无证书公钥加密,门限解密,随机预言模型

Abstract: Recommendation system is an effective way to solve the problem of information overloading and meanwhile satisfy user’s personalized needs.Nevertheless the data security issues involved from the recommendation procedure are definitely hindering the healthy development of recommendation system.In distributed recommendation systems,thre-shold decryption is one of the useful methods to resist security attack and protect user’s privacy.Regarding aforementioned techniques,we studied threshold decryption in the context of certificateless public key cryptography,aiming to avoid costly management of certificate in public key infrastructure and settle the matter of key escrow in identity-based cryptography.This paper introduced a new construction for certificateless threshold decryption scheme and the corresponding security model.The scheme was proved secure against chosen-ciphertext attack in the random oracle model and the security proof was presented under the condition of hard computation of a problem in relation to bilinear diffie-hellman problem.Compared with other existing schemes,our scheme has lower computational overhead,faster transmission rate and shorter master secret key and public key.The scheme can not only improve the efficiency of recommendation system but also effectively ensure the safety of user’s privacy.

Key words: Recommendation system,Data security,Certificateless public key encryption,Threshold decryption,Random oracle model

朱俊,袁晓峰,勾智楠,杨亿. 面向推荐系统数据安全的无证书门限解密方案[J]. 计算机科学, 2017, 44(11): 253-263. https://doi.org/10.11896/j.issn.1002-137X.2017.11.038

ZHU Jun, YUAN Xiao-feng, GOU Zhi-nan and YANG Yi. Certificateless Threshold Decryption Scheme for Data Security of Recommendation System[J]. Computer Science, 2017, 44(11): 253-263. https://doi.org/10.11896/j.issn.1002-137X.2017.11.038

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