With the development of the intelligent and connected automobile industry, vehicles have become important information terminals integrated into the interconnection system. The data generated by intelligent and connected vehicles (ICVs) has many application scenarios and rapid changes. And there are lots of potential risks which threats the security of data. The data includes a large amount of personal information, such as vehicle trajectory data and in-vehicle camera video data. In order to avoid the risk of personal privacy security caused by the leakage, this paper analyzes the security risks in the data lifecycle, and chooses eight typical scenarios of ICVs data security, including Internet of Vehicles (IoV) data extraction, vehicle-machine data transfer, and three-party data sharing. A data security testing method for ICVs based on typical scenarios is proposed. This work contributes to discover and solve data security issues in ICVs and provides strong support for the security of ICVs.


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    Title :

    Data Security Testing Method of Intelligent and Connected Vehicles Based on Typical Scenarios


    Contributors:
    Ji, Haojie (author) / Wang, Jingyan (author) / Wang, Liyong (author) / Sun, Guowei (author) / Jin, Long (author) / Fang, Junzhe (author)


    Publication date :

    2023-10-28


    Size :

    1430114 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English






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