An improved authentication protocol for self-driving vehicles based on Diffie–Hellman algorithm

   Authentication is a critical challenge in autonomous vehicles, particularly within Controller Area Networks which are prone to various cyber threats. Existing protocols often fall short in balancing strong security guarantees with computational efficiency and privacy preservation. In this paper,...

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Veröffentlicht in:Nauchno-tekhnicheskiĭ vestnik informat͡s︡ionnykh tekhnologiĭ, mekhaniki i optiki Jg. 25; H. 4; S. 755 - 761
Hauptverfasser: Saeed, Muhammad Salman, Bezzateev, S. V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: ITMO University 29.08.2025
Schlagworte:
автономные транспортные средства
механизмы сохранения анонимности
протокол аутентификации
сети контроллеров
эффективная аутентификация
ISSN:2226-1494, 2500-0373
Online-Zugang:Volltext
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Zusammenfassung:   Authentication is a critical challenge in autonomous vehicles, particularly within Controller Area Networks which are prone to various cyber threats. Existing protocols often fall short in balancing strong security guarantees with computational efficiency and privacy preservation. In this paper, we propose a lightweight authentication protocol based on the Decisional Diffie–Hellman problem, specifically designed for Controller Area Network environments. The protocol employs lightweight cryptographic operations to verify vehicle authenticity and validate data messages, while also maintaining anonymity by regularly updating login identities. It also supports password changes without requiring a trusted third party. The protocol security is formally verified using Burrows-Abadi-Needham logic. Performance evaluation shows that our approach significantly reduces computational overhead, achieving an execution time of 0.90908 ms, outperforming existing solutions in the literature. By combining formal verification with practical efficiency, the proposed protocol offers a robust solution for secure and efficient authentication in resource-constrained vehicular networks. Its lightweight design and anonymity-preserving mechanisms make it particularly suitable for real-time autonomous vehicle applications.
ISSN:2226-1494
2500-0373
DOI:10.17586/2226-1494-2025-25-4-755-761