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

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Part of the book series:Lecture Notes in Computer Science ((LNSC,volume 11634))

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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 bisectingk-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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Author information

Authors and Affiliations

  1. Nanjing University of Post and Telecommunication, Nanjing, 210023, China

    Hua Dai, Yan Ji & Geng Yang

  2. Jiangsu Security and Intelligent Processing Lab of Big Data, Nanjing, 210023, China

    Hua Dai & Geng Yang

  3. Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Liang Liu

  4. Royal Melbourne Institute of Technology University, Melbourne, 3001, Australia

    Xun Yi

Authors
  1. Hua Dai

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  2. Yan Ji

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  3. Liang Liu

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  4. Geng Yang

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  5. Xun Yi

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Corresponding author

Correspondence toHua Dai.

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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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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