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Conference Papers Year : 2019

CaTch: A Confidence Range Tolerant Misbehavior Detection Approach

Joseph Kamel
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  • PersonId : 1031548
Arnaud Kaiser
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Ines Ben Jemaa
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Pierpaolo Cincilla
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  • PersonId : 1014832


Misbehavior detection is a challenging problem that needs to be addressed in vehicular communications. Misbe-havior detection consists of monitoring the semantic of the exchanged messages to identify potential misbehaving entities. This is achieved by performing plausibility and consistency checks on exchanged beacon and warning messages. However, existing misbehavior detection solutions ignore the mandatory information on data inaccuracy, being gathered by the vehicular sensors. In this paper, we propose CaTch, an embedded misbehavior detection solution that integrates data inaccuracy when performing plausibility and consistency checks. Through extensive simulations, we show that CaTch is able to attribute an accurate uncertainty factor to misbehaving nodes and that it performs better than the state-of-the-art solutions.
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Dates and versions

hal-02126960 , version 1 (13-05-2019)


  • HAL Id : hal-02126960 , version 1


Joseph Kamel, Arnaud Kaiser, Ines Ben Jemaa, Pierpaolo Cincilla, Pascal Urien. CaTch: A Confidence Range Tolerant Misbehavior Detection Approach. IEEE Wireless Communications and Networking Conference, Apr 2019, Marrakech, Morocco. ⟨hal-02126960⟩
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