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An Extensible and Effective Anonymous Batch Authentication Scheme for Smart Vehicular Networks

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journal contribution
posted on 11.03.2020, 14:15 by Jing Zhang, Hong Zhong, Jie Cui, Yan Xu, Lu Liu
    In recent years, research on the security of Industry 4.0 and the Internet of Things (IoT) has attracted close attention from industry, government and the scientific community. Smart vehicular networks, as a type of industrial IoT, inevitably exchange large amounts of security and privacy-sensitive data, which make them attractive targets for attackers. For protecting network security and privacy, we have proposed an extensible and effective anonymous batch authentication scheme. In contrast to traditional pseudonym authentication schemes, the same system private key need not to be preloaded in our scheme, effectively avoiding a system failure when destroying a vehicle. Besides, the certificate revocation list (CRL) size is merely related to the number of vehicles that have been revoked, regardless of the number of pseudonym certificates for revoked vehicles. Moreover, this scheme maintains the effectiveness of the traditional scheme, effectively reduces the scale of the CRL, and employs an identity revocation scheme that supports rapid distribution. The scheme supports conditional privacy protection, namely, only the trusted authority (TA) can uniquely trace and revoke vehicles. For illegal vehicles, the TA releases the two hashed seeds to facilitate traceability by all entities in its domain. Furthermore, security analysis indicates that our solution is secure under the random oracle model and fulfills a series of security requirements of vehicular networks. Compared to existing authentication schemes, performance evaluations show that the scheme offers relatively good performance in terms of time consumption.


The work was supported by the National Natural Science Foundation of China (No.61872001, No.61702005), the Key Program of National Natural Science Foundation of China (No. U1936220), the Open Fund of Key Laboratory of Embedded System and Service Computing (Tongji University), Ministry of Education (No. ESSCKF2018-03), the Open Fund for Discipline Construction, Institute of Physical Science and Information Technology, Anhui University and the Excellent Talent Project of Anhui University.



IEEE Internet of Things Journal, 2020

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School of Informatics


AM (Accepted Manuscript)

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IEEE Internet of Things Journal


Institute of Electrical and Electronics Engineers (IEEE)



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