Defense against SSDF Attack and PUE Attack in CR-Internet of Vehicles (IoVs) for Millimeter Wave Massive MIMO Beamforming Systems

The Internet of Vehicles (IoV) is witnessed to play the leading role in future Intelligent Transportation Systems (ITS). Though many works have focused on IoV improvement, there still a lack performance due insufficient spectrum availability, lower data rates, and involvement attackers. This paper considers all three issues by developing novel mmWave-assisted Cognitive Radio based (CR-IoV) model. integration CR resolves issue management, while mmWave technology ensures symmetry acquiring higher rates for Secondary Users (SUs). With proposed CR-IoV model, symmetric improvements network were achieved main areas: security, beamforming, routing. Optimum detection mechanisms isolate malicious (SUs) overall network. First, Spectrum Sensing Data Falsification (SSDF) attack detected Hybrid Kernel-based Support Vector Machine (HK-SVM), which lightweight Learning (ML) technique. Then, Primary User Emulation (PUE) hybrid approach, namely Fang Algorithm-based Time Difference Arrival (FA-TDoA) method. Further, security assured validating legitimacy each SU through Lightweight ID-based Certificate Validation mechanism. To accomplish this, we employed Four Q-curve asymmetric cryptographic algorithm. Overall, dual-step provisioning approach assures that free from Next, beamforming performed legitimate SUs 3D-Beamforming algorithm relies Array Factor (AF) Beampattern Function. Finally, routing enabled formulating Forwarding Zone (FZ) forwarding angle. In zone, optimal forwarders are selected Multi-Objective Whale Optimization (MOWO) Here, new potential score formulated fitness evaluation. model validated extensive simulations ns-3.26 simulation tool. evaluation shows better terms throughput, packet delivery ratio, delay, bit error rate, accuracy.