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Misbehavior Detection in C-ITS: A comparative approach of local detection mechanisms

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Joseph Kamel
  • Function : Author
  • PersonId : 1031548
Ines Ben Jemaa
  • Function : Author
Arnaud Kaiser
  • Function : Author
Loic Cantat
  • Function : Author
  • PersonId : 751231
  • IdHAL : loic-cantat

Abstract

MisBehavior Detection (MBD) is an important security mechanism in Cooperative Intelligent Transport Systems (C-ITS). It involves monitoring C-ITS communications to detect potentially misbehaving entities. This monitoring is based on local plausibility and consistency checks done by the Intelligent Transport Systems (ITS) Station (ITS-S) on every received Vehicle-to-Everything (V2X) message. These checks are then analyzed by a local detection mechanisms to estimate the overall plausibility of a message. In this paper we focus on the logic behind different local detection mechanisms. First, we propose different local detection solutions based on logics extracted from the state of the art. Then we present a comparative review of the detection quality and the computation latency of each proposed mechanisms.
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Dates and versions

hal-02400137 , version 1 (09-12-2019)

Identifiers

  • HAL Id : hal-02400137 , version 1

Cite

Joseph Kamel, Ines Ben Jemaa, Arnaud Kaiser, Loic Cantat, Pascal Urien. Misbehavior Detection in C-ITS: A comparative approach of local detection mechanisms. Vehicular Networking Conference (VNC), Dec 2019, Los Angeles, California, United States. ⟨hal-02400137⟩
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