AI-Enhanced Secure Communication using Blockchain Decentralized Zero Trust Authentication Mechanism with Quantum Bio-Inspired Approach for CRNs
Abstract
Cognitive Radio Networks (CRNs) are a new era of wireless communication systems that enable secondary users to access spectrum bands opportunistically when primary users are not using them. Although a CRN can provide high-quality service and enhance spectrum utilization, there are still some important urgent problems to be solved, such as insecure communication, malicious nodes participating in the network, and unreliable routing performance. However, none of the existing security and communication schemes can achieve trusted entity validation, shortest-path optimization, and communication reliability simultaneously in CRNs. To address these challenges, this paper presents the AI assisted Blockchain Decentralized Zero Trust Authentication (BDZTA) approach for secure communication in CRN. Initially, the proposed Trust-Energy Aware Transmission Node Assessment (TEATNA) method is employed to identify the reliable transmission nodes. Then, the Adaptive Graph Neural Network (AGNN) model is used to classify the optimal shortest communication path by capturing the dynamic topological structure among cognitive radio nodes. After optimal route selection, Quantum-Inspired Whale Optimization with Elliptic Curve Cryptography (QIWO-ECC) approach is utilised for key generation and lightweight data encryption. Subsequently, the BDZTA approach is used to enable secure, decentralized communication through continuous identity verification. Finally, the Proof of Authority Verification (PoAV) scheme is used to validate authorized communication entities and ensure secure participation in transactions. The integrated framework significantly improves secure communication, trusted routing, Packet Delivery Ratio (PDR), energy efficiency, end-to-end delay, and energy consumption. The results of the experimental analysis show that the proposed approach achieves the best performance among existing schemes, thereby providing strong, reliable, and intelligent communication in CRNs.