Severity of Attacks in a Vehicle Platoon by Model-Based Simulation

This work explores model-based attack injection technique to analyse the severity of attacks to a platoon made of autonomous vehicles. Once the model of the cyber-physical system has been defined and built, we proceed to the identification of the threats that may be used to exploit the vulnerabilities of the control system of the autonomous car. Then we design driving and attack scenarios, and run several simulations in case of platoon under attack. We explore different combinations of attack parameters and driving scenarios by using the Design Space Exploration. Finally, we use the collected simulation traces to improve the knowledge on the resiliency of the system to the attacks; as well as to gauge the severity of the attacks and the possible relations between the attack parameter and the effect on the overall behavior of the system. The methodology provides quantitative evidence for risk assessment and reveals critical vulnerabilities in platoon coordination mechanisms.