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.
This research was supported by the National Natural Science Foundation of China under the grant Nos. 61872197, 61572263, 61772285, 61672297 and 61872193; the Postdoctoral Science Foundation of China under the Grant No. 2019M651919; the Natural Science Foundation of Anhui Province under grant No. 1608085MF127; the Natural Research Foundation of Nanjing University of Posts and Telecommunications under the grand No. NY217119.
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Dai, H., Ji, Y., Liu, L., Yang, G., Yi, X. (2019). A Privacy-Preserving Multi-keyword Ranked Search over Encrypted Data in Hybrid Clouds. In: Sun, X., Pan, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2019. Lecture Notes in Computer Science(), vol 11634. Springer, Cham. https://doi.org/10.1007/978-3-030-24271-8_7
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