, Volume 98, Issue 7, pp 685–708 | Cite as

LESPP: lightweight and efficient strong privacy preserving authentication scheme for secure VANET communication

  • Mingzhong Wang
  • Dan Liu
  • Liehuang Zhu
  • Yongjun Xu
  • Fei Wang


Authentication in vehicular ad-hoc network (VANET) is still a research challenge, as it requires not only secure and efficient authentication, but also privacy preservation. In this paper, we proposed a lightweight and efficient authentication scheme (LESPP) with strong privacy preservation for secure VANET communication. The proposed scheme utilizes self-generated pseudo identity to guarantee both privacy preservation and conditional traceability, and it only requires a lightweight symmetric encryption and message authentication code (MAC) generation for message signing and a fast MAC re-generation for verification. Compared with currently existing public key based schemes, the proposed scheme significantly reduces computation cost by \(10^2\)\(10^3\) times and decreases communication overhead by 41.33–77.60 %, thus achieving resilience to denial of service (DoS) attack. In LESPP, only key management center can expose a vehicle’s real identity from its pseudo identity, therefore, LESPP provides strong privacy preservation so that the adversaries cannot trace any vehicles, even if all roadside units are compromised. Furthermore, vehicles in LESPP need not maintain certificate revocation list (CRL), so any CRL related overhead is avoided. Extensive simulations reveal that the novel scheme is feasible and has an outstanding performance of nearly 0 ms network delay and 0 % packet loss ratio, which are especially appropriate for realtime emergency event reporting applications.


Secure VANET communication Lightweight authentication   Strong privacy preservation Conditional traceability DoS resilience 

Mathematics Subject Classification




This paper is supported by Program for New Century Excellent Talents in University (NCET-12-0046), National Natural Science Foundation of China No.61272512, Beijing Municipal Natural Science Foundation No.4121001, and DNSLAB, China Internet Network Information Center, Beijing 100190.


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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • Mingzhong Wang
    • 1
  • Dan Liu
    • 1
  • Liehuang Zhu
    • 1
  • Yongjun Xu
    • 2
  • Fei Wang
    • 2
  1. 1.School of Computer ScienceBeijing Institute of TechnologyBeijingPeople’s Republic of China
  2. 2.Institute of Computing TechnologyChinese Academy of SciencesBeijingPeople’s Republic of China

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