TY - GEN
T1 - Detection of Cyber-Attacks in Collaborative Intersection Control
AU - Keijzer, Twan
AU - Jarmolowitz, Fabian
AU - Ferrari, Riccardo M.G.
N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2021
Y1 - 2021
N2 - Road intersections are widely recognized as a lead cause for accidents and traffic delays. In a future scenario with a significant adoption of Cooperative Autonomous Vehicles, solutions based on fully automatic, signage-less Intersection Control would become viable. Such a solution, however, requires communication between vehicles and, possibly, the infrastructure over wireless networks. This increases the attack surface available to a malicious actor, which could lead to dangerous situations. In this paper, we address the safety of Intersection Control algorithms, and design a Sliding-Mode-Observer based solution capable of detecting and estimating false data injection attacks affecting vehicles’ communication. With respect to previous literature, a novel detection logic with improved detection performances is presented. Simulation results are provided to show the effectiveness of the proposed approach.
AB - Road intersections are widely recognized as a lead cause for accidents and traffic delays. In a future scenario with a significant adoption of Cooperative Autonomous Vehicles, solutions based on fully automatic, signage-less Intersection Control would become viable. Such a solution, however, requires communication between vehicles and, possibly, the infrastructure over wireless networks. This increases the attack surface available to a malicious actor, which could lead to dangerous situations. In this paper, we address the safety of Intersection Control algorithms, and design a Sliding-Mode-Observer based solution capable of detecting and estimating false data injection attacks affecting vehicles’ communication. With respect to previous literature, a novel detection logic with improved detection performances is presented. Simulation results are provided to show the effectiveness of the proposed approach.
UR - http://www.scopus.com/inward/record.url?scp=85124884306&partnerID=8YFLogxK
U2 - 10.23919/ECC54610.2021.9655088
DO - 10.23919/ECC54610.2021.9655088
M3 - Conference contribution
SN - 978-1-6654-7945-5
SP - 62
EP - 67
BT - Proceedings of the European Control Conference (ECC 2021)
PB - IEEE
T2 - 2021 European Control Conference (ECC)
Y2 - 29 June 2021 through 2 July 2021
ER -