Quantum-Resilient Blockchain-Integrated Covert Authentication for UAV Networks with AI-Driven Consensus Mechanism

The rapid expansion of Unmanned Aerial Vehicle (UAV) networks necessitates robust security frameworks to mitigate vulnerabilities such as identity theft, information leakage, and brute-force attacks. Traditional authentication mechanisms often rely on public channel identity verification, exposing them to security risks. Blockchain technology provides a decentralized, tamper-proof solution, yet existing consensus mechanisms suffer from scalability issues in dynamic UAV environments. This paper proposes a Quantum-Resilient Blockchain-Integrated Covert Authentication (Q-BICA) mechanism, which enhances UAV security by leveraging covert communication and an AI-driven quantumresistant consensus protocol. Identity information is transmitted via covert tags embedded in standard modulated signals, significantly reducing susceptibility to eavesdropping and brute-force decryption. Furthermore, an AI-Optimized Quantum-Resilient Practical Byzantine Fault Tolerance (AI-QRPBFT) consensus algorithm is introduced, where machine learning (ML) dynamically adjusts node weights based on UAV behavior, historical authentication outcomes, and real-time channel conditions, while employing lattice-based cryptographic techniques to resist quantum computing attacks. This approach enhances fault tolerance, scalability, and future-proof security in large-scale UAV networks. Simulation results demonstrate that Q-BICA outperforms existing authentication models in terms of security robustness, network scalability, and resilience under low Signal-to-Noise Ratio (SNR) conditions. The proposed mechanism represents a novel integration of covert authentication with an AI-driven quantum-resilient blockchain consensus, ensuring secure and