Alleviating Congestion Attacks on Traffic Signal Systems

This work addresses congestion attacks on prioritization and preemption signal applications (PPSA), an important variant of cooperative intelligent transport systems (C-ITS). In PPSA, priority vehicles, such as buses and ambulances, can request traffic signal adjustments in their favor to reduce travel time. These systems rely on vehicle-to-everything (V2X) communications, which makes them vulnerable to congestion attacks. When under attack, these systems experience disruptions in information exchange between vehicles and infrastructure, leading to traffic congestion and safety hazards. Nevertheless, existing solutions do not address the attacks at a system level and within the PPSA context. Our proposal presents a software framework designed to enhance both sustainability and safety during congestion attacks. Specifically, it introduces a whitelist-based traffic-filtering mechanism that preserves system sustainability by ensuring only legitimate priority requests are processed. Additionally, a monitoring mechanism evaluates the PPSA service rate at runtime to identify and address potential safety risks arising from insufficient service rates. Moreover, we analyze the limitations of a machine learning-based defense method and highlight risks of potential service unavailability due to false positives. We believe that this research contributes to the development of a secure and safe traffic management system for smart cities.