Anti-Jamming V2V Communication in an Integrated UAV-CAV Network with Hybrid Attackers

Abstract

Connected and autonomous vehicles (CAVs) and unmanned aerial vehicles (UAVs) are viewed as revolutionary technologies in the era of Internet of Things (IoT). However, both CAV and UAV can be exploited by potential adversaries and pose serious threats to the intelligent transportation system (ITS), such as damaging the vehicle-to-vehicle (V2V) communication. In this paper, we investigate the anti-jamming V2V communication in an integrated UAV-CAV network with hybrid attackers, which consist of a malicious CAV with intelligent jamming capability and a malicious UAV without. To solve this problem, we propose to use a unique research tool named cognitive dynamic system (CDS), and apply its function of cognitive risk control (CRC) to develop an effective countermeasure. In each perception-action cycle (PAC), the power control will always be performed by a legitimate transmitting vehicle; meanwhile, the process of channel selection only takes place if the risk level is evaluated as high after completing the power control. This kind of design that involves task-switching is inspired by the predictive-adaptation feature of the human brain. Simulation results have shown that the proposed method based on CRC is able to defend hybrid attackers effectively under various settings.