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Secure vehicle traffic data dissemination and analysis protocol in vehicular cloud computing

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Abstract

Intelligent transportation systems seek to maximize the usage of data generated by the vehicles for road users assistance. Combining vehicular ad hoc network with cloud computing makes it easy for the fixed infrastructures along the roads to collect and analyze safety messages for the benefits of the road users and the transportation authorities. However, security features need to be fully assessed before the adoption of such applications. In this paper, we present a secure vehicle traffic data dissemination and analysis in vehicular cloud computing in which the identity privacy of the vehicles and their generated message is achieved through pseudonym techniques. We use anonymous credential to guarantee the authorization of service demanding vehicles. ID-based signature is applied to assure the authentication of the vehicles for given pseudonyms. The efficient verification of signature on the message and revoked vehicles are achieved through batch verification technique and pseudonymous revocation list, respectively. Traffic estimation methods are applied to mine coarse-grained data collected by road side infrastructures. The merits of the proposed protocol compared to existing ones are shown through extensive simulations.

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIP) (No. NRF-2014R1A2A1A11052981).

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Authors and Affiliations

  1. Department of IT Convergence and Application Engineering, Pukyong National University, Busan, Republic of Korea

    Lewis Nkenyereye, Youngho Park & Kyung-Hyune Rhee

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  1. Lewis Nkenyereye
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  2. Youngho Park
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  3. Kyung-Hyune Rhee
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Correspondence to Kyung-Hyune Rhee.

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Nkenyereye, L., Park, Y. & Rhee, KH. Secure vehicle traffic data dissemination and analysis protocol in vehicular cloud computing. J Supercomput 74, 1024–1044 (2018). https://doi.org/10.1007/s11227-016-1773-0

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  • DOI: https://doi.org/10.1007/s11227-016-1773-0

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