Skip to Main content Skip to Navigation
Journal articles

Simulation Framework for Misbehavior Detection in Vehicular Networks

Abstract : Cooperative Intelligent Transport Systems (C-ITS) is an ongoing technology that will change our driving experience in the near future. In such systems, vehicles and RoadSide Unit (RSU) cooperate by broadcasting V2X messages over the vehicular network. Safety applications use these data to detect and avoid dangerous situations on time. MisBehavior Detection (MBD) in C-ITS is an active research topic which consists of monitoring data semantics of the exchanged Vehicle-to-X communication (V2X) messages to detect and identify potential misbehaving entities. The detection process consists of performing plausibility and consistency checks on the received V2X messages. If an anomaly is detected, the entity may report it by sending a Misbehavior Report (MBR) to the Misbehavior Authority (MA). The MA will then investigate the event and decide to revoke the sender or not. In this paper, we present a MisBehavior Detection (MBD) simulation framework that enables the research community to develop, test, and compare MBD algorithms. We also demonstrate its capabilities by running example scenarios and discuss their results. Framework For Misbehavior Detection (F 2 MD) is open source and available for free on our github.
Complete list of metadata

Cited literature [35 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02527873
Contributor : Joseph Kamel <>
Submitted on : Wednesday, April 1, 2020 - 3:10:41 PM
Last modification on : Thursday, December 10, 2020 - 4:47:19 PM

File

F2MD-TVT.pdf
Files produced by the author(s)

Identifiers

Citation

Joseph Kamel, Mohammad Raashid Ansari, Jonathan Petit, Arnaud Kaiser, Ines Ben Jemaa, et al.. Simulation Framework for Misbehavior Detection in Vehicular Networks. IEEE Transactions on Vehicular Technology, Institute of Electrical and Electronics Engineers, In press, IEEE Transactions on Vehicular Technology, 69 (6), pp.6631-6643. ⟨10.1109/TVT.2020.2984878⟩. ⟨hal-02527873⟩

Share

Metrics

Record views

494

Files downloads

1511