Conditional Privacy-Preserving Multi-Domain Authentication and Pseudonym Management for 6G-Enabled IoV

With the emergence of the sixth-generation (6G) communication technologies, the Internet of Vehicles (IoV) is rapidly developing with the coordination between intelligent networked vehicles, road infrastructures, and the cloud. However, the openness and dynamic nature of the IoV raise significant se...

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Bibliographic Details
Published in:IEEE transactions on information forensics and security 2024-01, Vol.19, p.10206-10220
Main Authors: Cheng, Guanjie, Huang, Junqin, Wang, Yewei, Zhao, Jun, Kong, Linghe, Deng, Shuiguang, Yan, Xueqiang
Format: Article
Language:English
Subjects:
6G mobile communication
Authentication
Blockchains
conditional privacy preservation
Costs
identity-based signature
Internet of Vehicles
Merkle tree
Privacy
pseudonym management
Security
Vehicle-to-everything
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Summary:With the emergence of the sixth-generation (6G) communication technologies, the Internet of Vehicles (IoV) is rapidly developing with the coordination between intelligent networked vehicles, road infrastructures, and the cloud. However, the openness and dynamic nature of the IoV raise significant security and privacy concerns, highlighting the need for efficient authentication schemes. Conventional authentication schemes are no longer suitable for 6G-enabled IoV due to high latency, single point of failure, and heavy management costs. Additionally, existing literature on multi-domain authentication mainly investigates vehicle mobility, ignoring the challenges posed by vehicle heterogeneity. To fill this gap, we propose a multi-domain authentication scheme with conditional privacy preservation (MACPP) that considers administrative domains (AD) and geographic domains (GD) in the IoV. In MACPP, we design a novel identity-based signature scheme without requiring bilinear pairing for efficient authentication. Additionally, we propose a blockchain-assisted pseudonym management scheme (BAPM) to further improve system security by designing a dynamical sparse Merkle tree structure (DSMT). We demonstrate that the proposed MACPP satisfies the security requirements through an in-depth security analysis. Moreover, the experimental results demonstrate the effectiveness and efficiency of both MACPP and BAPM.
ISSN:1556-6013
1556-6021
DOI:10.1109/TIFS.2023.3314211