期刊
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
卷 19, 期 5, 页码 3478-3493出版社
IEEE COMPUTER SOC
DOI: 10.1109/TDSC.2021.3101120
关键词
Privacy; Servers; Data privacy; Cloud computing; Encryption; Computational modeling; Encoding; Multi-dimensional range query; cloud computing; encrypted data; single-dimensional privacy; R-tree
类别
资金
- NSERC [04009]
- Natural Science Foundation of Shaanxi Province [2019ZDLGY12-02]
- ZJNSF [LZ18F020003]
- NSFC [U1709217, 61972304]
This article proposes a practical and privacy-preserving multi-dimensional range query (PRQ) scheme, which utilizes R-tree and lightweight matrix encryption technique to address the issues of single-dimensional privacy leakage, inefficiency, and the requirement of two cloud servers in existing solutions.
It is undeniable that Internet of Things (IoT) in big data era can provide us with huge volumes of multi-dimensional data, transforming our society into a much more intelligent one. In order to fit for the multi-dimensional data processing in big data era, multi-dimensional range queries, especially over cloud platform, have received considerable attention in recent years. However, as the cloud server is not fully trustable, designing multi-dimensional range queries over encrypted data becomes a research trend, and many solutions have been proposed in the literature. Nevertheless, most existing solutions suffer from the leakage of the single-dimensional privacy, and such leakage would severely put the data at risk. Although a few existing works have addressed the problem of single-dimensional privacy, they are impractical in some real scenarios due to the issues of inefficiency, inaccuracy, and two-cloud-server requirement. Aiming at solving these issues, in this article, we propose a practical and privacy-preserving multi-dimensional range query (PRQ) scheme. Specifically, in our proposed PRQ scheme, we first index the multi-dimensional dataset with an R-tree and reduce R-tree based range queries to the problem of point intersection and range intersection. Then, by employing the lightweight matrix encryption technique, we design two novel algorithms for PRQ, i.e., multi-dimensional point intersection predicate encryption (PIPE) and multi-dimensional range intersection predicate encryption (RIPE), which can preserve the privacy of the proposed point intersection algorithm and range intersection algorithm, and further preserve the single-dimensional privacy of the proposed PRQ scheme. Detailed security analysis shows that our proposed PRQ scheme is indeed privacy-preserving. In addition, extensive simulations are conducted, and the results also demonstrate its efficiency.
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