Misbehavior detection system in VANETs using local traffic density

Publikationstyp
Conference Paper
Date Issued
2018-12
Sprache
English
Author(s)
Zacharias, Jithin  
Fröschle, Sibylle  orcid-logo
TORE-URI
http://hdl.handle.net/11420/9664
Article Number
8628321
Citation
IEEE Vehicular Networking Conference (VNC 2018)
Contribution to Conference
IEEE Vehicular Networking Conference, VNC 2018  
Publisher DOI
10.1109/VNC.2018.8628321
Scopus ID
2-s2.0-85062548694
In this paper we explore a novel approach for misbehavior detection in Vehicular Ad-Hoc Networks (VANETs) using local traffic density. The approach is based on measuring local traffic density from two independent sensors and representing it as evidence for certain traffic situation. Dempster rule of combination is used for fusing together multiple pieces of evidence from reliable and unreliable sensors to detect the misbehavior. The approach is particularly suited to detect illusion attacks, which is still a challenge for vehicular communication. We motivate and discuss the approach and demonstrate its potential by an example scenario considering illusion attack.
Subjects
illusion attack
local traffic density
Misbehavior Detection System
Sensor fusion
VANET Security