In Vehicular Ad-Hoc Networks (VANETs), the exchange of location data (i.e. absolute position, heading, time) for traffic safety applications plays an important role. The trustworthiness of this information is crucial as false data affects applications heavily and might endanger human lives. Beside cryptographic solutions that ensure sender authenticity and message integrity, the data plausibility check is an important mechanism to ensure positional reliability. In this paper, we show that a particle filter is an appropriate instrument to perform plausibility checks in order to assess the trustworthiness of neighbor nodes. Our approach allows the aggregation of information from different data sources directly in one particle filter per neighbor. Thus, dependencies and relationships between individual sources can be fully accounted for and the framework is easily extensible and scales well. The concept is implemented as a Java-OSGi bundle for a field operational test framework and evaluated using both manually generated traces and recorded data from real vehicle trips. We show that the detection of several types of location-based attacks is possible under consideration of errors and system inherent deviations in sensor data.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Assessment of node trustworthiness in VANETs using data plausibility checks with particle filters


    Contributors:


    Publication date :

    2012-11-01


    Size :

    601236 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Automatic adjust cuts filters checks

    Montgomerie,G. / SAB Svenska AB Bromsregulator,SE | Automotive engineering | 1978


    Plausibility checking method

    SIEMENS ANTON | European Patent Office | 2015

    Free access



    Sensor plausibility using GPS road information

    LEACH WILLIAM / PAULI KURT / PIETZSCH SYLVIA | European Patent Office | 2024

    Free access