Blockchain-enhanced UAV networks for post-disaster communication: A decentralized flocking approach

Hafeez, S ORCID: 0000-0003-4769-4284, Cheng, R ORCID: 0000-0001-6410-8975, Mohjazi, L, Sun, Y ORCID: 0000-0002-4391-377X and Imran, MA (2025) Blockchain-enhanced UAV networks for post-disaster communication: A decentralized flocking approach. Digital Communications and Networks. ISSN 2352-8648

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Abstract

Unmanned Aerial Vehicles (UAVs) have significant potential for agile communication and relief coordination in post-disaster scenarios, especially when conventional ground infrastructure is compromised. However, effectively coordinating and securing swarms of heterogeneous UAVs from multiple service providers presents critical challenges related to privacy, scalability, lightweight consensus protocols, and cybersecurity resilience. This study proposes a blockchain-enabled UAV coordination framework that leverages consensus mechanisms, smart contracts, and cryptographic techniques to address these challenges. First, a consortium blockchain architecture is introduced, integrating Zero-Knowledge Proofs (ZKPs) to enable privacy-preserving, multi-agency coordination while ensuring access control and data security. Second, a hybrid Delegated Proof-of-Stake–Practical Byzantine Fault Tolerance (DPoS-PBFT) consensus protocol is developed to optimise security, efficiency, and resilience against node failures in resource-constrained UAV networks. Third, a decentralized flocking algorithm is proposed to enable adaptive and autonomous UAV cluster operations under dynamically changing connectivity conditions, ensuring seamless disaster relief functions. Comprehensive simulations show that the proposed system scales efficiently to 500 UAV nodes while maintaining high throughput and low latency, with only a 50-ms increase in latency from 10 to 500 nodes. The framework demonstrates strong cyber resilience, remaining robust under denial-of-service (DoS), spoofing, and tampering attacks. Furthermore, communication latencies remain under 10 milliseconds, with median values of approximately 2–3 ms, achieved through self-optimizing network intelligence. The results validate the proposed system as a secure, scalable, and high-performance solution for UAV-enabled disaster response, ensuring reliable emergency communication and efficient resource allocation in critical environments.

Item Type:	Article
Uncontrolled Keywords:	4605 Data Management and Data Science; 4606 Distributed Computing and Systems Software; 46 Information and Computing Sciences; 4604 Cybersecurity and Privacy; 11 Sustainable Cities and Communities; 0805 Distributed Computing; 1005 Communications Technologies; 1203 Design Practice and Management; 4006 Communications engineering; 4606 Distributed computing and systems software
Subjects:	Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > T Technology (General) > T58.5 Information Technology
Divisions:	Computer Science and Mathematics
Publisher:	Elsevier
Date of acceptance:	20 March 2026
Date of first compliant Open Access:	7 July 2026
Date Deposited:	07 Jul 2026 08:53
Last Modified:	07 Jul 2026 08:53
DOI or ID number:	10.1016/j.dcan.2026.03.006
URI:	https://researchonline.ljmu.ac.uk/id/eprint/28950

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