Vehicular crowdsensing networks play a critical role in the Internet of Vehicles by enabling efficient information services, but challenges like on-demand message authentication and privacy protection persist. We propose a secure crowdsensing scheme, TRAMS, based on multi-authority attribute-based signatures, enabling fine-grained policies for participant authentication while safeguarding vehicle privacy. TRAMS incorporates a multi-authority key management system to enhance sensing efficiency, achieving superior message authentication compared to single-authority systems. To address malicious behaviors in VANETs, we introduce HDRS, a hybrid reputation system where vehicles and roadside units independently evaluate reputations and cross-reference results. HDRS leverages a reliability module and a dynamic adjustment mechanism to counter intelligent attacks, achieving up to 30% higher detection rates for collusion and 16% for adaptive threats compared to existing solutions.


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    Titel :

    Secure Vehicular Crowdsensing and Malicious Vehicles Detection in VANETs


    Weitere Titelangaben:

    Advd Topics Sci.,Technology China


    Beteiligte:
    Xia, Yingjie (Autor:in) / Liu, Xuejiao (Autor:in) / Wu, Huihui (Autor:in) / Li, Qichang (Autor:in)


    Erscheinungsdatum :

    20.02.2025


    Format / Umfang :

    49 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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