AutoDetect

AutoDetect is a research project funded by the State-Foundation Baden-Württemberg in which we investigate misbehavior detection mechanisms in automotive systems. The goal of our research is the development of approaches and mechanisms which can detect data and sensor values injected by attackers in internal vehicular networks and V2X communication by different detectors. Detectors can be based on consistency and plausibility checks and used to rate, filter, or even correct data. To this end, we develop a framework based on subjective logic.

Project Publications


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van der Heijden, Rens Wouter; Dietzel, Stefan; Leinmüller, Tim; Kargl, Frank
Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems
IEEE Communications Surveys & Tutorials,
October 2018
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van der Heijden, Rens W.; Lukaseder, Thomas; Kargl, Frank
VeReMi: A Dataset for Comparable Evaluation of Misbehavior Detection in VANETs
SecureComm'18,
August 2018
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van der Heijden, Rens W.; Kopp, Henning; Kargl, Frank
Multi-Source Fusion Operations in Subjective Logic
Proceedings of the 21st International Conference on Information Fusion
Publisher: IEEE,
July 2018
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van der Heijden, Rens W.; Engelmann, Felix; Mödinger, David; Schönig, Franziska; Kargl, Frank
Blackchain: Scalability for Resource-Constrained Accountable Vehicle-to-X Communication
SERIAL'17: SERIAL'17: ScalablE and Resilient InfrAstructures for distributed Ledgers, December 11--15, 2017, Las Vegas, NV, USA
December 2017
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van der Heijden, Rens W.; Lukaseder, Thomas; Kargl, Frank
Analyzing Attacks on Cooperative Adaptive Cruise Control (CACC)
Proceedings of the IEEE Vehicular Technology Conference (VNC) (Best Paper Award)
Publisher: IEEE,
November 2017
ISBN: 978-1-5386-0986-6
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van der Heijden, Rens W.; Kargl, Frank
Evaluating Misbehavior Detection for Vehicular Networks
Proceedings of 5th GI/ITG KuVS Fachgespräch Inter-Vehicle Communication (FG-IVC 2017)
April 2017
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Persons

Lead

Prof. Dr. Frank Kargl

Staff

Rens van der Heijden

Status

Duration 1.1.2011 - 31.12.2014