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A mutual authentication scheme in VANET providing vehicular anonymity and tracking

Author

Listed:
  • Jiabei He

    (Hunan University of Science and Technology)

  • Xuchong Liu

    (Hunan Police Academy)

  • Fan Wu

    (Xiamen Institute of Technology)

  • Chaoyang Chen

    (Hunan University of Science and Technology)

  • Xiong Li

    (University of Electronic Science and Technology of China)

Abstract

Nowadays, the intelligent transportation system (ITS) has developed prosperously all over the world. As a key technique in ITS, vehicular ad-hoc network (VANET) supports fast transmitting while bringing security problems simultaneously. To ensure efficiency, those unprotected data transmitting at a high speed can be easily eavesdropped on or forged, which will badly damage the ITS. To authenticate the identities of the vehicles in VANETs, signatures with certificates are often employed in historical research, but seldom study discusses the protection of generated data or mutual authentication between participants in VANETs. In order to tackle the problems above, we propose a new mutual authentication scheme for VANET where the private data can be kept away from attackers. In our scheme, the corresponding manager of each region can deal with the dynamic information of vehicles. The security analysis is also carried out and shown to emphasize the reliability of the scheme, such as anonymity, unlinkability and resistance to replay attacks, etc. Besides the resistance to different attacks, the real-time information secrecy can also be protected in our scheme, which is not achieved in the compared schemes. Moreover, the performance evaluation and simulation with NS-3 show that the packet delivery ratio reaches over 99% in most of the application scenarios, which proves that the scheme is efficient and practical.

Suggested Citation

  • Jiabei He & Xuchong Liu & Fan Wu & Chaoyang Chen & Xiong Li, 2022. "A mutual authentication scheme in VANET providing vehicular anonymity and tracking," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 81(2), pages 175-190, October.
    • Handle: RePEc:spr:telsys:v:81:y:2022:i:2:d:10.1007_s11235-022-00911-4
    DOI: 10.1007/s11235-022-00911-4
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    References listed on IDEAS

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    1. Kaffash, Sepideh & Nguyen, An Truong & Zhu, Joe, 2021. "Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 231(C).
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