The recent trend of integrating vehicular communications with advanced sensors installed on vehicles, enables Connected and Autonomous Vehicles (CAVs) to share their own driving information as well as perception information, such as a list of perceived objects (e.g., dynamic obstacles such as vehicles, pedestrians, and cyclists, and static obstacles). This has the potential to improve driving safety by expanding collective perception of vehicles. However, adversaries may also populate false information to other Connected Vehicles (CVs) via Vehicle-to-Vehicle (V2V) communications. This paper investigates the security aspects of mixed deployment of CAVs, CVs and legacy vehicles, and in particular with regards to misbehavior detection. We provide a generic design framework that is independent from the specific algorithms of the underlying perception system, and can be used to implement a practical Misbehavior Detection System (MDS). We analyze the MDS framework w.r.t. a ghost vehicle attack. While no computing system can be completely secure, we believe this work would help the industry to develop a practical MDS design within a common framework while allowing individual techniques to mature and evolve over time with future academic research.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Design of a Misbehavior Detection System for Objects Based Shared Perception V2X Applications


    Contributors:


    Publication date :

    2019-10-01


    Size :

    800340 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Local perception and BSM based misbehavior detection in Intelligent Transportation System

    Gyawali, Sohan / Shimizu, Takayuki / Lu, Hongsheng et al. | IEEE | 2022


    MISO- V: Misbehavior Detection for Collective Perception Services in Vehicular Communications

    Liu, Xiruo / Yang, Lily / Alvarez, Ignacio et al. | IEEE | 2021


    MISBEHAVIOR DETECTION USING DATA CONSISTENCY CHECKS FOR COLLECTIVE PERCEPTION MESSAGES

    YANG LIUYANG / ALVAREZ IGNACIO J / LIU XIRUO et al. | European Patent Office | 2022

    Free access


    CONTEXT-ADAPTIVE RSSI-BASED MISBEHAVIOR DETECTION

    CHEN CONG / PETIT JONATHAN / ANSARI MOHAMMAD RAASHID | European Patent Office | 2022

    Free access