面向混合云的可并行多关键词Top-k密文检索技术

随着云计算技术的迅猛发展,越来越多的企业和个人青睐使用私有云和公有云相结合的混合云环境,用于外包存储和管理其私有数据。为了保护外包数据的私密性,数据加密是一种常用的隐私保护手段,但这同时也使得针对加密数据的搜索成为一个具有挑战性的问题。文中提出了面向混合云的可并行的多关键词Top-k密文检索方案。该方案通过对文档、关键词分组进行向量化处理,并引入对称加密和同态矩阵加密机制,保护外包数据的私密性,同时支持多关键词密文检索;通过引入MapReduce计算模式,使得公有云和私有云合作完成的密文检索过程能够按照并行化方式执行,从而能够支持针对大规模加密数据的并行化检索。安全分析和实验结果表明,提出的检索方案能够保护外包数据的隐私,且其检索效率优于现有的同类方案。

Parallel Multi-keyword Top-k Search Scheme over Encrypted Data in Hybrid Clouds

With the rapid development of cloud computing services,more and more individuals and enterprises prefer to outsource and manage their data or computation to clouds.In order to protect the privacy of outsourced data,encryption before outsourcing is a commonly measure.However,it is a challenge to perform searches over encrypted data.In this paper,we propose a parallel privacy-preserving multi-keyword Top-k search scheme over encrypted data in hybrid clouds.The scheme can protect the privacy of outsourced data and support multi-keyword search over encrypted data,which performs vectorization on documents and keyword groups and introduces the symmetric encryption and the homomorphic matrix encryption.In addition,the scheme adopts the MapReduce model to perform parallel searches in the public clouds and the private clouds.Thus,parallel searches over the large scale encrypted data are achieved.The security analysis and the performance evaluation show that the proposed scheme is a privacy-preserving multi-keyword Top-k search scheme and outperforms the existing scheme in terms of search ef ciency.