Abstract
With the rapid development of cloud computing services, more and more individuals and enterprises prefer to outsource their data or computing to clouds. In order to preserve data privacy, the data should be encrypted before outsourcing and it is a challenge to perform searches over encrypted data. In this paper, we propose a privacy-preserving multi-keyword ranked search scheme over encrypted data in hybrid clouds, which is denoted as MRSE-HC. The keyword dictionary of documents is clustered into balanced partitions by a bisecting $k$ -means clustering based keyword partition algorithm. According to the partitions, the keyword partition based bit vectors are adopted 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. On the basis of the MRSE-HC scheme, an enhancement scheme EMRSE-HC is proposed, which adds complete binary pruning tree to further improve search efficiency. The security analysis and performance evaluation show that MRSE-HC and EMRSE-HC are privacy-preserving multi-keyword ranked search schemes for hybrid clouds and outperforms the existing scheme FMRS in terms of search efficiency.
Highlights
Nowadays, the cloud computing technology is considered as a rapid developing and popular model of distributed computing and storage, which has the advantages of high-quality data storage, quick and convenient computing and ‘‘on-demand service’’, etc
PERFORMANCE EVALUATION we evaluate the performance of our proposed basic scheme MRSE-HC, efficiency enhanced scheme EMRSE-HC and compare them with the scheme presented in [26] which is denoted as FMRS
Most of the existing multi-keyword ranked search over encrypted data are for the public cloud
Summary
The cloud computing technology is considered as a rapid developing and popular model of distributed computing and storage, which has the advantages of high-quality data storage, quick and convenient computing and ‘‘on-demand service’’, etc. We propose a privacy-preserving multikeyword ranked search over encrypted data in hybrid clouds. H. Dai et al.: Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds k-means clustering algorithm and multiple balanced partitions are generated. In the search stage, when a query having multi-keywords is started, the corresponding QFB-vector and trapdoor are respectively generated and submitted to Pri-Cloud and Pub-Cloud. (2) On the basis of the keyword partition vector model and the complete binary tree structure, we propose an efficient ranked search scheme over encrypted data in hybrid clouds. The result shows that the proposed scheme is a privacy-preserving multi-keyword ranked search scheme for hybrid clouds and outperforms the existing scheme FMRS in terms of search efficiency
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