Fully Autonomous vehicles (AV) are estimated to reach consumers widely in the near future. The manufacturers will have to be completely sure that AVs can outperform human drivers, which first of all requires a solid model of the world surrounding the car. Emerging trends for perception models in the automobile industry seems to be towards combining the data from LiDAR and camera in Multi-Sensor Fusion (MSF). Making the perception model reliable in the event of unforeseen real world circumstances is tricky enough, but the real challenge comes from the security issue that arises when ill-intentioned people try to attack sensors. In this article, we take a deep dive into the possible attacks and countermeasures for LiDAR and camera. We discuss it in the context of MSF, and provide a simple framework for further analysis, which we conclude will be needed in order to conceptualize a truly safe AV.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Analysis of Sensor Attacks against Autonomous Vehicles



    Erscheinungsdatum :

    2023-01-01


    Anmerkungen:

    Bønning Jakobsen , S , Sylvest Knudsen , K & Andersen , B 2023 , Analysis of Sensor Attacks against Autonomous Vehicles . in Proceedings of the 8th International Conference on Internet of Things, Big Data and Security - IoTBDS . vol. 1 , SCITEPRESS Digital Library , pp. 131-139 , 8th International Conference on Internet of Things, Big Data and Security , Prague , Czech Republic , 21/04/2023 . https://doi.org/10.5220/0011841800003482



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629