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A secure and lightweight privacy-preserving data aggregation scheme for internet of vehicles

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Abstract

Data aggregation can effectively improve resource utilization in Internet of Vehicles (IoV), and has attracted broad attention recently. However, because of the particularity of nodes in IoV, data aggregation faces security challenges such as location privacy, data privacy and accuracy of aggregation results. To solve these challenges, in this paper, we propose a secure and lightweight privacy-preserving data aggregation scheme, named SLPDA, for IoV. Specifically, SLPDA employs Chinese Remainder Theorem to map multi-dimensional data to one-dimensional data, and uses masking technology to encrypt data, thus roadside units can realize lightweight data aggregation without plaintext. SLPDA also adopts Identity-based batch authentication technology to reduce authentication overhead. Detailed security analysis indicates that SLPDA can resist various security threats. In addition, the performance evaluations demonstrate that SLPDA is more efficient than the reported schemes in terms of computation complexity and communication overhead.

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Acknowledgments

This article has been awarded by the National Natural Science Foundation of China (61170035, 61272420, 81674099, 61502233), the Fundamental Research Fund for the Central Universities (30916011328, 30918015103), Nanjing Science and Technology Development Plan Project (201805036), and “13th Five-Year” equipment field fund (61403120501).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

    Peng Hu, Yongli Wang, Ruxin Zhao, Hao Li & Bo Li

  2. CETC Big Data Research Institute Co., Ltd, Guiyang, 550081, China

    Yongli Wang

  3. College of Computer Science, Beijing University of Technology, Beijing, 100124, China

    Bei Gong

  4. National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, 100029, China

    Yongjian Wang

  5. School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Yanchao Li

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  1. Peng Hu
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  2. Yongli Wang
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  3. Bei Gong
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  4. Yongjian Wang
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  5. Yanchao Li
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  6. Ruxin Zhao
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  7. Hao Li
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  8. Bo Li
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Correspondence to Yongli Wang.

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Hu, P., Wang, Y., Gong, B. et al. A secure and lightweight privacy-preserving data aggregation scheme for internet of vehicles. Peer-to-Peer Netw. Appl. 13, 1002–1013 (2020). https://doi.org/10.1007/s12083-019-00849-6

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  • DOI: https://doi.org/10.1007/s12083-019-00849-6

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