We develop an extensible platform for exploring cyber-attacks on connected and autonomous vehicle (CAV) platoon controllers. A unique feature of our platform is the ability to address a large spectrum of cyber threats, including new attacks designed after deployment. This platform facilitates systematic exploration of cyber-attacks, helping to uncover real-time vulnerabilities across different designs of platoon controllers. Additionally, we introduce a novel, dual-stage detection mechanism that employs a time-series machine learning (ML) model for the real-time detection of attacks on the perception channels of a Model Predictive Control (MPC)-based CAV platoon. We present extensive experimental results to showcase the effectiveness and feasibility of our approach.


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    Titel :

    Exploration and Detection of Cyber-Attacks on MPC-Based Vehicular Platoons


    Beteiligte:
    Choudhury, Tashfique (Autor:in) / Duan, Chengwei (Autor:in) / Zhang, Hanyu (Autor:in) / Du, Lili (Autor:in) / Ray, Sandip (Autor:in)


    Erscheinungsdatum :

    24.09.2024


    Format / Umfang :

    2661928 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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