Intelligent Transportation Systems (ITS) is one of the challenging research areas revolving around rapid communication services. Nonetheless, these networks are afflicted by congestion, routing, and security issues, particularly in urban areas, which result in delay and computational complexity issues and late message delivery or data congestion. Sensitive data are collected and transmitted over public channels, which presents challenges for security and authentication. Moreover, the security of ITS-smart vehicle communication is impacted by the complexity of discrete logarithm and factoring problems, which could make data transmission and authentication very difficult in the presence of highly scalable quantum computers. Hence, we present a novel, secure and verifiable post-quantum data transmission and authentication protocol for ITS (RAVEN), specifically designed for smart automobiles. The RAVEN scheme incorporates a discrete Gaussian distribution and lattice-based cryptosystem for enhanced performance and security. We use the formal verification method SVO logic and an informal security analysis against passive and active assaults to validate the security of mutual authentication. The use of a well-known automated AVISPA tool allowed for a further evaluation of the scheme’s security soundness. The OMNeT++ simulator is used to evaluate the efficacy of the RAVEN scheme in terms of end-to-end delay, throughput, and energy consumption. The evaluation findings demonstrate that the suggested method achieves reduced costs in terms of computation and communication compared to existing schemes but with comprehensive security that can greatly benefit ITS.


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    Title :

    RAVEN: Robust Anonymous Vehicular End-to-End Encryption and Efficient Mutual Authentication for Post-Quantum Intelligent Transportation Systems



    Published in:

    Publication date :

    2024-11-01


    Size :

    9100286 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English