TriP: Misbehavior Detection for Dynamic Platoons Using Trust

Abstract

Platooning is able to improve fuel efficiency and reduce road congestion. But to maximize the concept's impact, platoons need to be created dynamically whenever feasible. Therefore, vehicles have to cooperate with unknown and possibly malicious partners, creating new safety hazards. Hence, vehicles need to be able to determine the trustworthiness of their cooperators. This paper proposes TriP, a trust model which rates platoon members by the divergence of their reported to their actual behavior. The proposed model is evaluated against attacks from literature. The evaluation demonstrates that TriP detects all attacks and prevents harm by deploying countermeasures thus mitigating safety hazards.