Thwarting SSDF Attacks From High-Speed Movement VUs in the CIoV Network: Based on Blockchain and Stochastic Evolutionary Game

Cognitive Internet of Vehicles (CIoV) adds the cognitive engine based on traditional Internet of Vehicles (IoV), which can improve spectrum utilization. However, spectrum sensing data falsification (SSDF) attacks pose a threat to CIoV network security. To ensure the full utilization of spectrum resources and protect primary users transmission, this article combines blockchain with CIoV to defend against SSDF attacks in the presence of vehicle users (VUs) entering and leaving the network. Specifically, this article introduces a virtual currency called Sencoins serve as credential for VUs to purchase transmission shares. And this article proposes a reward and punishment mechanism and a hybrid Proof-of-Stake (PoS) and Proof-of-Work (PoW) mining model to thwart the motivation of the VUs to launch SSDF attacks. On this basis, this article investigates the dynamics of SSDF attack strategy choice of VUs, and uses the largest Lyapunov exponent (LLE) to determine the critical value of Sencoins that avoids the system to exhibit chaotic behavior. To describe the uncertainty of the population proportion of VUs that choose different attack strategies due to high-speed movement and the VUs entering and leaving the CIoV network, this article introduces Gaussian white noise into the replication dynamics equation and builds the Itô stochastic evolutionary game model, and solves it according to the stability judgment theorem of stochastic differential equations and stochastic Taylor expansion. Finally, simulation results verify that the proposed method can quickly and effectively thwart SSDF attacks in the CIoV network. And compared with traditional methods, the proposed method can improve the efficiency of defending against SSDF attacks by 567% and the average throughput by 25%.