On Cybersecurity of Freeway Control Systems: Analysis of Coordinated Ramp Metering Attacks

Abstract

This article focuses on cybersecurity of transportation systems and investigates their vulnerability to attacks on the sensing and control infrastructure. An array of different attack points, classified into physical, close-proximity, and virtual layers, are reviewed and investigated. The authors construct two benchmark scenarios which exploit these vulnerabilities to identify the potential harm of a traffic control system compromise. A more in-depth analysis is then presented on the takeover of a series of networked onramp metering traffic lights. The analysis is conducted using a methodology for precise and intelligent onramp metering attacks based on finite-horizon optimal control techniques and multi-objective optimization. The methodology is demonstrated in simulation for two examples of high-level attack objectives: congestion-on-demand, which aims to create precise pockets of congestion on a model of the I15 San Diego freeway, and catch-me-if-you-can, which attempts to aid a fleeing vehicle from chasing pursuants.