Detection of Cyber-Attacks in Collaborative Intersection Control

Conference paper (2021)

Authors

T. Keijzer Team Riccardo Ferrari - Mechanical, Maritime and Materials Engineering
Fabian Jarmolowitz Robert Bosch GmbH
Riccardo M.G. Ferrari Team Riccardo Ferrari - Mechanical, Maritime and Materials Engineering
Research Group
Team Riccardo Ferrari (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2021 T. Keijzer, Fabian Jarmolowitz, Riccardo M.G. Ferrari
DOI
help_outline
https://doi.org/10.23919/ECC54610.2021.9655088
More Info
expand_more

Published Date

2021

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Riccardo Ferrari

Abstract

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.