Design and Analysis of Blockchain Assisted Authentication and Collision Avoidance Mechanisms for Unmanned Aerial Vehicle Networks

Unmanned Aerial Vehicle (UAV) networks are emerging as a critical component of modern communication systems, supporting diverse applications ranging from disaster response and surveillance to intelligent transportation and commercial services. But UAVs operate within very dynamic and resource-constrained environments characterized by limited computational ability, energy restraints, and evolving adversarial threats. Ensuring secure and efficient communication, particularly in authentication and collision avoidance has remained a significant challenge. Conventional approaches relying on centralized infrastructures or heavy cryptographic operations are unsuitable for rapidly moving aerial networks due to excessive latency and computational cost. A blockchain-assisted, lightweight, and decentralized communication framework for UAV networks is developed and validated through simulation-based study to address these challenges. The initial phase of the study examines the feasibility of blockchain integration in UAV networks under varying aerial mobility, node density, and data rates. Performance is analyzed in terms of throughput, latency, coverage area, and data rate under varying conditions. The analysis demonstrates that blockchain is feasible for UAV networks and the lightweight consensus methods can significantly improve scalability and reduce overhead. Building on these insights, the second major contribution introduces a lightweight two-way authentication protocol designed to establish mutual trust among UAVs while minimizing different costs. Experimental benchmarking demonstrates that our lightweight blockchainbased two-way mutual authentication scheme reduces authentication latency by approximately 40% and decreases computational overhead by about 35% relative to prominent UAV authentication methods that rely only on a single authentication mechanism. The results confirm that the proposed scheme achieves lower communication cost compared to state-of-the-art methods while maintaining resistance against replay, impersonation, and man-in-the-middle attacks. The third major contribution fosters a decentralized collision detection and avoidance framework that integrates blockchain with UAV telemetry. Potential collisions are anticipated, and safe maneuvering decisions are enforced in real time through smart contracts, where positional data is validated and securely distributed to support optimal maneuvering. Improved collision avoidance is demonstrated through performance analysis, along with reduced collision probability and an extraordinary packet delivery rate of 99.7%. The resilience of the proposed contributions against adversarial threats are validated through comprehensive security analysis, with confidentiality, integrity, authenticity, and non-repudiation being ensured. Comparative, simulation-based validation against state-of-the-art approaches demonstrates that the proposed blockchain-assisted framework effectively mitigates cyber threats while achieving lower latency, reduced computational overhead, and improved scalability in dynamic UAV networks.