Evaluating Cybersecurity Risks of Cooperative Ramp Merging in Mixed Traffic Environments

TL;DR

This paper assesses cybersecurity risks in cooperative highway on-ramp merging with connected vehicles, demonstrating how cyber-attacks can impair traffic performance and proposing a defense strategy to enhance system resilience.

Contribution

It introduces threat models with trajectory spoofing, evaluates attack impacts using a specialized simulator, and proposes a mitigation algorithm to improve cybersecurity resilience in mixed traffic environments.

Findings

Mobility performance drops up to 55.19% under attack.

Cyber-attacks degrade safety and energy efficiency.

Proposed defense significantly improves attack resilience.

Abstract

Connected and Automated Vehicle (CAV) technology has the potential to greatly improve transportation mobility, safety, and energy efficiency. However, ubiquitous vehicular connectivity also opens up the door for cyber-attacks. In this study, we investigate cybersecurity risks of a representative cooperative traffic management application, i.e., highway on-ramp merging, in a mixed traffic environment. We develop threat models with two trajectory spoofing strategies on CAVs to create traffic congestion, and we also devise an attack-resilient strategy for system defense. Furthermore, we leverage VENTOS, a Veins extension simulator made for CAV applications, to evaluate cybersecurity risks of the attacks and performance of the proposed defense strategy. A comprehensive case study is conducted across different traffic congestion levels, penetration rates of CAVs, and attack ratios. As expected, the results show that the performance of mobility decreases up to 55.19% at the worst case when the attack ratio increases, as does safety and energy. With our proposed mitigation defense algorithm, the system's cyber-attack resiliency is greatly improved.