Detection of Cyber-Attacks in Collaborative Intersection Control

TL;DR

This paper proposes a novel detection method using a Sliding-Mode-Observer to identify false data injection attacks in wireless communication for autonomous vehicle intersection control, enhancing safety in future intelligent transportation systems.

Contribution

It introduces a new detection logic with improved performance for identifying cyber-attacks on vehicle communication in autonomous intersection management.

Findings

Effective detection of false data injection attacks demonstrated in simulations.

Improved detection performance over previous methods.

Potential to enhance safety in autonomous vehicle intersection control.

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.