Efficient k-NN query over encrypted data in cloud with limited key-disclosure and offline data owner

被引:40
|
作者
Zhou, Lu [1 ,2 ]
Zhu, Youwen [2 ,3 ]
Castiglione, Aniello [4 ]
机构
[1] Shandong Univ, Jinan 250100, Shandong, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing 211106, Jiangsu, Peoples R China
[3] Collaborat Innovat Ctr Novel Software Technol & I, Nanjing 210021, Jiangsu, Peoples R China
[4] Univ Salerno, Dept Comp Sci, I-84084 Fisciano, Italy
基金
中国国家自然科学基金;
关键词
Outsourcing; Privacy; Cloud computing; k-Nearest neighbors; Query; ALGORITHM; NETWORK; SEARCH; SERVICES;
D O I
10.1016/j.cose.2016.11.013
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Several schemes for k-nearest neighbors (k-NN) query over encrypted data in cloud have been proposed recently. Nevertheless, existing schemes either suppose each query user is fully-trusted, or need data owner to be online for each query. A fully-trusted query user is assumed to obtain the decryption key of data owner's outsourced dataset, thus, cloud, server could entirely break the outsourced dataset upon gaining the decryption key from some untrustworthy query user. Because of the online requirement, data owner still needs to burden too many computational tasks during the k-NN queries, which thus is impractical. In this paper, we propose a new scheme to perform k-NN query over encrypted data in cloud while protecting the privacy of both data owner and query users from cloud. Our new method just reveals limited information about data owner's key to query users, and has no need of an online data owner. For gaining the properties, we present a new scalar product protocol, then the new protocol and some other transformation approaches are merged into our secure k-NN query system. Additionally, we confirm our security and efficiency through theoretical analysis and extensive simulation experiments. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:84 / 96
页数:13
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