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Privacy-preserving content-based image retrieval in edge environment

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Abstract

Traditional centralized cloud services face challenges, such as high communication delay, single point of failure, etc. Edge computing is one of distributed computing services in which resources are placed closer to users, and thus is more robust and can reduce communication delay. Although outsourcing data to the edge servers can bring great convenience, it also brings serious security threats. In order to provide image retrieval while ensuring users’ data privacy, a privacy-preserving content-based image retrieval scheme in edge environment is proposed. Considering the distributed characteristics of edge environment and the requirement of lightweight computing, we design a secure interaction protocol completed through the collaborative cooperation of two or more edge servers. This scheme not only protects data privacy, but also has low communication overhead and delay as well as low computing complexity, therefore it is more suitable for edge computing environment. Theoretical analysis and experiments show that our scheme has high security, retrieval accuracy and efficiency.

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Data availability

The datasets that support the finding of this paper, i.e., Corel1K, Corel10K and GHIM20, are publicly available datasets, which can be obtained for scientific research and are available in the http://wang.ist.psu.edu/docs/related.shtml, http://www.ci.gxnu.edu.cn/cbir/Dataset.aspx.

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Funding

This research is supported by the National Natural Science Foundation of China (No. 41571426), National Key Research and Development Program of China under Grant (No. 2017YFB0504202).

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Authors and Affiliations

  1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China

    Yuejing Yan, Yanyan Xu, Yiran Zhang, Zhiheng Wang & Zheheng Rao

  2. Key Laboratory of Aerospace Information Security and Trusted Computing of the Ministry of Education, Wuhan University, Wuhan, 430079, China

    Yanyan Xu

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  1. Yuejing Yan
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  4. Zhiheng Wang
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Contributions

All authors have made great contributions to the research. The main design of the work, the analysis of data and the revising of the work were performed by YY and YX. The first draft of the manuscript and the experiments were finished by YY. YZ, ZW, and ZR assisted in data collection, data presentation and manuscript correction. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yanyan Xu.

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Yan, Y., Xu, Y., Zhang, Y. et al. Privacy-preserving content-based image retrieval in edge environment. Cluster Comput 25, 363–381 (2022). https://doi.org/10.1007/s10586-021-03404-2

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