CaTch: A Confidence Range Tolerant Misbehavior Detection Approach - Archive ouverte HAL Access content directly
Conference Papers Year :

CaTch: A Confidence Range Tolerant Misbehavior Detection Approach

(1) , (1) , (1) , (1) , (2, 3)
1
2
3
Joseph Kamel
  • Function : Author
  • PersonId : 1031548
Arnaud Kaiser
  • Function : Author
Ines Ben Jemaa
  • Function : Author
Pierpaolo Cincilla
  • Function : Author
  • PersonId : 1014832

Abstract

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.
Fichier principal
Vignette du fichier
Catch.pdf (1.06 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

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

Identifiers

  • HAL Id : hal-02126960 , version 1

Cite

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⟩
566 View
450 Download

Share

Gmail Facebook Twitter LinkedIn More