Assessing and mitigating cybersecurity risks of traffic light systems in smart cities

Abstract

Intelligent traffic lights are critical cyber-physical systems that help smart cities to cut road congestion and vehicle emissions. However, they also open a new frontier of cybersecurity. Security researchers have demonstrated ways to compromise the traffic lights to cause potential traffic disruption and public safety degradation. This study aims to raise the public awareness of the cybersecurity issues in traffic light systems. The authors present a bi-level game-theoretic framework for assessing cybersecurity risks of traffic light systems, as the first step towards understanding and mitigating the security vulnerabilities. Additionally, they propose a minimax-regret-based methodology to guide the deployment of defensive measures in traffic light systems against cyberattacks.

Keywords

• security of data
• road traffic
• smart cities
• road safety
• game theory
• minimax techniques
• intelligent transportation systems
• cybersecurity risk assessment
• cybersecurity risk mitigation
• traffic light systems
• smart cities
• intelligent traffic lights
• cyber-physical systems
• road congestion
• vehicle emissions
• traffic disruption
• public safety degradation
• public awareness
• bilevel game-theoretic framework
• security vulnerabilities mitigation
• minimax-regret-based methodology
• cyberattacks