Many Intrusion Detection approaches for Vehicular ad hoc networks (VANETs) are proposed. However, not moving fake vehicles and vehicles with a plausible mobility model are not considered in other approaches. In this paper we propose an innovative signature based intrusion detection method that verifies vehicle movement data by applying a plausibility model. With our approach a single fake vehicle can be identified based on the plausibility model even if it simulates an autonomously valid movement. The results from the intrusion detection can be used to detect on the one hand road side attackers simulating faked traffic congestions and on the other hand attackers that try to deny real congestions by inserting moving vehicles into the network.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Intrusion detection in VANETs through verification of vehicle movement data


    Contributors:
    Bissmeyer, N (author) / Stresing, C (author) / Bayarou, K M (author)


    Publication date :

    2010-12-01


    Size :

    282304 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Intrusion detection in VANETs through verification of vehicle movement data

    Bißmeyer, N. / Stresing, C. / Bayarou, K.M. | Fraunhofer Publica | 2010

    Free access

    Intrusion detection in VANETs through verification of vehicle movement data

    Bißmeyer, N. / Stresing, C. / Bayarou, K.M. | DataCite | 2010


    Sustainable Learning-Based Intrusion Detection System for VANETs

    Wei, Lu / Yang, Jie / Jin, Hulin et al. | IEEE | 2025


    Collaborative Intrusion Detection for VANETs: A Deep Learning-Based Distributed SDN Approach

    Shu, Jiangang / Zhou, Lei / Zhang, Weizhe et al. | IEEE | 2021