Enhanced position verification for VANETs using subjective logic
Van der Heijden, Rens W.
Abu-Sharkh, Osama M. F.
FakultätFakultät für Ingenieurwissenschaften, Informatik und Psychologie
InstitutionInstitut für Verteilte Systeme
Ressourcen- / MedientypKonferenzveröffentlichung, Text
Datum der Erstveröffentlichung2016-03-31
The integrity of messages in vehicular ad-hoc networks has been extensively studied by the research community, resulting in the IEEE 1609.2 standard, which provides typical integrity guarantees. However, the correctness of message contents is still one of the main challenges of applying dependable and secure vehicular ad-hoc networks. One important use case is the validity of position information contained in messages: position verification mechanisms have been proposed in the literature to provide this functionality. A more general approach to validate such information is by applying misbehavior detection mechanisms. In this paper, we consider misbehavior detection by enhancing two position verification mechanisms and fusing their results in a generalized framework using subjective logic. We conduct extensive simulations using VEINS to study the impact of traffic density, as well as several types of attackers and fractions of attackers on our mechanisms. The obtained results show the proposed framework can validate position information as effectively as existing approaches in the literature, without tailoring the framework specifically for this use case.Correction: revised the way an opinion is created with eART, and re-did the experiments (uploaded at arxiv as correction in agreement with TPC Chairs).
LCSHVehicular ad hoc networks (Computer networks)
Intrusion detection systems (Computer security)
Freie SchlagwörterMisbehavior detection
DDC-SachgruppeDDC 000 / Computer science, information & general works
OriginalpublikationRens W. van der Heijden, Ala'a Al-Momani, Frank Kargl, Osama M.F. Abu-Sharkh. Enhanced position verification for VANETs using subjective logic. Submitted on 30 Mar 2017 (v1), last revised 31 Mar 2017 (this version, v2), corrected version of a paper submitted to 2016 IEEE 84th Vehicular Technology Conference (VTC2016-Fall). Verfügbar bei arXiv.