Redundancy-based Statistical Analysis for Insider Attack Detection in VANET Aggregation Schemes

Stefan Dietzel, Julian Gürtler, Rens van der Heijden, Frank Kargl

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    10 Citations (Scopus)
    3 Downloads (Pure)


    In Vehicular Ad-hoc Networks (VANETs), vehicles exchange messages to enhance safety, driving efficiency, and comfort. The limited wireless channel capacity is a challenge especially for traffic efficiency applications, such as traffic in- formation systems. In such systems, a large number of traffic or road status observations needs to be disseminated quickly to interested vehicles, often via multi-hop forwarding and in a larger geographic area than what is needed for traffic safety applications. In-network aggregation protocols are a viable tool to enhance scalability of such applications. But from a security perspective, they open new attack vectors for insider attackers, because vehicles collaboratively merge and modify messages dur- ing dissemination. Moreover, countermeasures using too much communication bandwidth negatively affect scalability. In this paper, we present a bandwidth-efficient protection mechanism for in-network aggregation based on data-consistency checking. We combine data mining techniques to detect false information with a filtering technique for forwarding paths that limits the influence of attackers on aggregated data. Simulation results show that our approach can successfully detect common attacks on aggregation while maintaining bandwidth efficiency.
    Original languageEnglish
    Title of host publicationProceedings of the IEEE Vehicular Networking Conference 2014 (VNC 2014)
    Number of pages8
    ISBN (Print)978-1-4799-7660-7
    Publication statusPublished - Dec 2014
    EventIEEE Vehicular Networking Conference, VNC 2014 - Paderborn, Germany
    Duration: 3 Dec 20145 Dec 2014


    ConferenceIEEE Vehicular Networking Conference, VNC 2014
    Abbreviated titleVNC
    Internet address


    • EWI-25524
    • SCS-Cybersecurity
    • information aggregation
    • multi-hop communication
    • METIS-309792
    • Security
    • VANETS
    • IR-94313
    • EC Grant Agreement nr.: FP7/269994


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