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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    Title :

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


    Contributors:
    Wang, Liyong (author) / Jin, Long (author) / Ji, Haojie (author) / Chen, Yupeng (author) / He, Peng (author) / Wang, Jingyan (author) / Fang, Junzhe (author)

    Conference:

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


    Published in:

    CICTP 2024 ; 381-388


    Publication date :

    2024-12-11




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English