The diversity and complexity of typical scenarios of intelligent and connected vehicles (ICVs) bring serious risks to the data security of vehicles. To avoid the potential data security risks of ICVs effectively, this paper proposes a data risk analysis method for vehicles based on the characteristics of data assets. Considering the similarity between the internet of things (IoT) system and the internet of vehicles system, this method organizes the data assets of the vehicles combined with the layered architecture of the IoT system. The data security risks of vehicles are analyzed from the aspects of threat analysis, vulnerability analysis, and risk quantification. The risk points of vehicles are analyzed, so as to provide model design and verification methods for data security risk analysis of ICVs.


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    Titel :

    Research on Data Security Risk Analysis Method of Intelligent and Connected Vehicles Based on Data Asset


    Beteiligte:
    Wang, Liyong (Autor:in) / Jin, Long (Autor:in) / Ji, Haojie (Autor:in) / Chen, Yupeng (Autor:in) / He, Peng (Autor:in) / Wang, Jingyan (Autor:in) / Fang, Junzhe (Autor:in)

    Kongress:

    24th COTA International Conference of Transportation Professionals ; 2024 ; Shenzhen, China


    Erschienen in:

    CICTP 2024 ; 381-388


    Erscheinungsdatum :

    11.12.2024




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch