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Towards efficient privacy-preserving encrypted image search in cloud computing

  • Methodologies and Application
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Abstract

With the rapid development of cloud computing and big data, it is an ever-increasing trend to outsource the huge amount of multimedia data to the cloud. Although data outsourcing can alleviate data maintenance cost of user side, it inevitably brings some new security challenges, of which privacy of image content is the most significant one. Thus, privacy-preserving image search becomes a new research interest in academic community. In this paper, we propose a novel efficient search scheme for encrypted image by incorporating K-means and secure modular hashing, which can simultaneously achieve privacy-preserving of image search and comparable search accuracy to plaintext image. Furthermore, we provide comprehensively security analysis on the proposed solution and detailed efficiency evaluation over some real-world datasets. The results show that our solution can achieve desired security goals while providing a comparable search efficiency and accuracy.

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Acknowledgements

This study was funded by the National Natural Science Foundation of China (Nos. 61572382 and 61702401), China 111 Project (No. B16037), National Key Research and Development Program of China (No. 2017YFB0802202), National High Technology Research and Development Program (863 Program) of China (No. 2015AA01 6007), Key Project of Natural Science Basic Research Plan in Shannxi Province of China (No. 2016JZ021), China Postdoctoral Science Foundation (No. 2017M613083) and the CICAEET fund and the PAPD fund.

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Authors and Affiliations

  1. State Key Laboratory of Integrated Service Networks (ISN), Xidian University, Xi’an, People’s Republic of China

    Yuan Wang, Meixia Miao & Jianfeng Wang

  2. School of Computer and Software, Nanjing University of Information Science and Technology (NUIST), Nanjing, People’s Republic of China

    Jian Shen

  3. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, People’s Republic of China

    Jianfeng Wang

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  1. Yuan Wang
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  2. Meixia Miao
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  3. Jian Shen
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  4. Jianfeng Wang
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Correspondence to Jianfeng Wang.

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The authors declare that they have no conflict of interest.

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Communicated by V. Loia.

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Wang, Y., Miao, M., Shen, J. et al. Towards efficient privacy-preserving encrypted image search in cloud computing. Soft Comput 23, 2101–2112 (2019). https://doi.org/10.1007/s00500-017-2927-6

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