We lay ground for a comprehensive investigation of “traffic-related” threats to vehicular networks. While current research in the vehicular networks security area has done a good job in recognizing standard security and cryptographic threats, detailed modeling and analysis of threats that are specific to vehicle traffic are rarely considered in the literature. In this paper we study the problem of modeling traffic-related attacks in vehicular networks and presenting automatic and efficient (i.e., no human intervention and no expensive cryptographic protocols) solutions to prevent or tolerate a number of these attacks. To prevent these attacks, we propose techniques based on the capability of implementing simple and non-interactive voting algorithms using the mere participations of vehicles to the vehicular network. We provide analysis and simulation results in typical urban environments validating our techniques. Previous work required interactive protocols to implement voting or consensus techniques and implicitly left open the question we solve in this paper.


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    Title :

    Non-interactive malicious behavior detection in vehicular networks


    Contributors:
    Di Crescenzo, G (author) / Yibei Ling, (author) / Pietrowicz, S (author) / Tao Zhang, (author)


    Publication date :

    2010-12-01


    Size :

    189535 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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