Secure Traffic Lights: Replay Attack Detection for Model-based Smart Traffic Controllers
This addresses security risks in smart traffic management systems, which are critical for urban mobility and safety, but the work is incremental as it builds on existing attack detection methods.
The paper tackled vulnerabilities in model-based smart traffic controllers by demonstrating that false-data injection replay attacks can disrupt mobility and cause unsafe conditions, even with state-of-the-art attack detectors, using a VISSIM simulation of an isolated intersection.
Rapid urbanization calls for smart traffic management solutions that incorporate sensors, distributed traffic controllers and V2X communication technologies to provide fine-grained traffic control to mitigate congestion. As in many other cyber-physical systems, smart traffic management systems typically lack security measures. This allows numerous opportunities for adversarial entities to craft attacks on the sensor networks, wireless data sharing and/or the distributed traffic controllers. We show that such vulnerabilities can be exploited to disrupt mobility in a large urban area and cause unsafe conditions for drivers and the pedestrians on the roads. Specifically, in this paper, we look into vulnerabilities in model-based traffic controllers and show that, even with state-of-the-art attack detectors in place, false-data injection can be used to hamper mobility. We demonstrate a replay attack by modeling an isolated intersection in VISSIM, a popular traffic simulator and also discuss countermeasures to thwart such attacks.