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崔洋论文22-8-4.pdf (1.15 MB)

Lattice-based Batch Authentication Scheme with Dynamic Identity Revocation in VANET

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journal contribution
posted on 2022-08-30, 09:16 authored by F Li, Y Cui, J Wang, Huiyu Zhou, X Wang, Q Yang

Aggregate signatures allow someone to aggregate multiple signatures into one signature, which is suitable for resource-constrained and computationally inefficient environments. Identify-based aggregate signature can solve the storage problem of public key certificates while achieving efficient signature verification. However, in most of the identity-based aggregate signature schemes, the user identity revocation process is time-consuming and cannot resist quantum attacks. To solve above problems, this paper proposes a lattice-based aggregate signature scheme with dynamic identity revocation by combining lattice-based cryptography and an aggregate signature scheme. The security of the proposed lattice-based aggregate signature scheme with dynamic identity revocation has been proved in the random oracle model. In addition, the verification efficiency of the aggregate signature has been improved compared with multiple different signatures. Much of the data transfer in Vehicular Ad Hoc Network (VANET) is carried out wirelessly, which makes VANET vulnerable to identity spoofing attacks. Identity authentication technology can prevent attackers from impersonating legitimate users, thus ensuring the security of VANET. Based on the proposed lattice-based aggregate signature scheme with dynamic identity revocation, this paper proposes a lattice-based batch authentication scheme with dynamic identity revocation in VANET. Through the proposed batch authentication scheme, we can effectively resist the impersonation attack of VANET in the quantum computer environment, and the efficiency of authentication is improved.

History

Author affiliation

School of Informatics, University of Leicester

Version

  • AM (Accepted Manuscript)

Published in

International Journal of Intelligent Systems

Publisher

Wiley

issn

0884-8173

Acceptance date

2022-08-06

Copyright date

2022

Available date

2023-08-22

Language

en

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