A Privacy-Preserving Multi-keyword Ranked Search over Encrypted Data in Hybrid Clouds

Dai, H, Ji, Y, Liu, L, Yang, G and Yi, X 2019, 'A Privacy-Preserving Multi-keyword Ranked Search over Encrypted Data in Hybrid Clouds', in International Conference on Artificial Intelligence and Security, New York, NY, USA, July 2628 2019, pp. 68-80.


Document type: Conference Paper
Collection: Conference Papers

Title A Privacy-Preserving Multi-keyword Ranked Search over Encrypted Data in Hybrid Clouds
Author(s) Dai, H
Ji, Y
Liu, L
Yang, G
Yi, X
Year 2019
Conference name ICAIS 2019
Conference location New York, NY, USA
Conference dates July 2628 2019
Proceedings title International Conference on Artificial Intelligence and Security
Publisher Springer, Cham
Place of publication Melbourne
Start page 68
End page 80
Total pages 13
Abstract Due to the convenience, economy and high scalability of cloud computing, more and more individuals and enterprises are motivated to outsource their data or computing to clouds. In this paper, we propose a privacy-preserving multi-keyword ranked search over encrypted data in hybrid cloud, which is denoted as MRSE-HC. The keyword partition vector model is presented. The keyword dictionary of documents is clustered into balanced partitions by a bisecting k-means clustering based keyword partition algorithm. In accordance with the partitions, the keyword partition based bit vectors are defined for documents and queries which are utilized as the index of searches. The private cloud filters out the candidate documents by the keyword partition based bit vectors, and then the public cloud uses the trapdoor to determine the result in the candidates. The security analysis and performance evaluation show that MRSE-HC is a privacy-preserving multi-keyword ranked search scheme for hybrid clouds and outperforms the existing scheme FMRS in terms of search efficiency.
Subjects Data Encryption
Keyword(s) Hybrid cloud
Privacy-preserving
Multi-keyword ranked search
Searchable encryption
DOI - identifier 10.1007/978-3-030-24271-8_7
Copyright notice © Springer Nature Switzerland AG 2019
ISBN 9783030242718
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