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Efficient and secure k-nearest neighbor query on outsourced data

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Abstract

k-nearest neighbor (k-NN) query is widely applied to various networks, such as mobile Internet, peer-to-peer (P2P) network, urban road networks, and so on. The location-based service in the outsourced environment has become a research hotspot with the rise of cloud computing. Meanwhile, various privacy issues have been increasingly prominent. We propose an efficient privacy-preserving query protocol to accomplish the k-nearest neighbor (k-NN) query processing on outsourced data. We adopt the Moore curve to transform the spatial data into one-dimensional sequence and utilize the AES to encrypt the original data. According to the cryptographic transformation, the proposed protocol can minimize the communication overhead to achieve efficient k-NN query while protecting the spatial data and location privacy. Furthermore, the proposed efficient scheme offers considerable performance with privacy preservation. Experiments show that the proposed scheme achieves high accuracy and efficiency while preserving the data and location privacy when compared with the existing related approach.

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Acknowledgments

This work was supported by the National Key Research and Development Program of China under Grant 2017YFB0802704, 2017YFB0802202, and the National Natural Science Foundation of China under Grand 61972249.

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Authors and Affiliations

  1. School of Cyber Security, Shanghai Jiao Tong University, Shanghai, 200240, China

    Huijuan Lian, Weidong Qiu, Zheng Huang & Peng Tang

  2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Di Yan

Authors
  1. Huijuan Lian
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  2. Weidong Qiu
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  3. Di Yan
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  4. Zheng Huang
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  5. Peng Tang
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Correspondence to Weidong Qiu.

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This article is part of the Topical Collection: Special Issue on Security and Privacy in Machine Learning Assisted P2P Networks

Guest Editors: Hongwei Li, Rongxing Lu and Mohamed Mahmoud

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Lian, H., Qiu, W., Yan, D. et al. Efficient and secure k-nearest neighbor query on outsourced data. Peer-to-Peer Netw. Appl. 13, 2324–2333 (2020). https://doi.org/10.1007/s12083-020-00909-2

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  • DOI: https://doi.org/10.1007/s12083-020-00909-2

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