Detection and mitigation of vehicle platooning disruption attacks

Abstract

In response to the escalating challenges posed by traffic bottlenecks, accidents, and intersection delays, the deployment of platooning mechanisms emerges as an imperative remedy. This investigation revolves around a pivotal scenario wherein a closely-knit platoon of cooperative vehicles approaches an intersection. Orchestrated by a lead vehicle, this convoy navigates the traffic light to expedite the journey of its followers towards their respective destinations. However, given that the size of the platoon can be increased, it will become difficult for the leader to manage it smoothly. Therefore, dividing the platoon into small groups led by co-leaders who deal directly with the leader is considered an ideal solution to speed up and facilitate the process of maintaining platoon stability. In this paper, we propose a Cooperative Adaptive Platooning Control Algorithm (CAPCA) for the hybrid communication topology in platooning. In fact, CAPCA aims to achieve stability in the platoon by distributing tasks in a parallel manner to mini-platoons. Moreover, inherent complexities arise as select members within the platoon strive to undermine its stability. Within this context, the research addresses the intricacies of Vehicle Platooning Disruption (VPD) attacks, a menacing phenomenon characterized by deliberate efforts to destabilize or seize control of a platoon. These attacks manifest through tactics such as false data injection (FDI) and replaying of control messages. In response, a robust and multifaceted countermeasure is conceptualized. The Vehicle Platooning Disruption Attacks Detection Protocol (VPD-ADP) takes center stage as a foundational component. By identifying instability within the platoon's dynamics model, VPD-ADP lays the essential groundwork for mitigating the repercussions of FDI and replay attacks. Employing advanced stochastic time series analysis, the impact of VPD attacks is scrutinized via anomalies in the Cartesian coordinates of vehicles deviations from the trajectory anticipated by the platoon. Moreover, the study introduces the Reputation-based Reliable Mitigation Protocol (RRMP), a pioneering approach that leverages collaborative data gleaned from neighboring vehicles. RRMP is devised to assess the veracity of received messages and gauge their reliability in real-time. Through extensive simulations and experiments, the proposed approach's effectiveness in fortifying the resilience of vehicle platooning systems against an array of disruption attacks is convincingly demonstrated.