Blockchain-enabled identification friend or foe: a decentralized architecture for secure and resilient UAV operations

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Authors: Athanasios Koulianos, Αντώνιος Λίτκε, Nikolaos K. Papadakis
Cited by: 0
References: 27

Abstract

Accurate and secure Identification Friend or Foe (IFF) remains a fundamental component of contemporary military operations, particularly in light of the increasing deployment of unmanned aerial vehicles (UAVs). Traditional IFF systems, however, are predominantly centralized, rendering them susceptible to cyberattacks and single points of failure. To mitigate these vulnerabilities, this study proposes a three-layer blockchain architecture that distributes IFF functionalities across Edge, Regional, and Central nodes. Within this framework, local detections and lightweight block production are executed at the Edge layer, while Regional nodes aggregate these blocks to sustain theater-wide situational awareness. Final consensus is achieved at the Central layer through the Practical Byzantine Fault Tolerance (PBFT) protocol. By decentralizing trust and auditing mechanisms, the proposed architecture enhances resilience against spoofing and denial-of-service attacks, supporting robust friend-or-foe classification even in adversarial environments. The system’s performance is evaluated within a simulation environment where UAV state transitions follow a Markov-based model, subject to stochastic variations, and network communications adhere to an empirical channel model that accounts for path loss, shadowing, and fading. The results demonstrate that block production, transaction throughput, and consensus success rates scale effectively with an increasing number of regions and Edge nodes, affirming the architecture’s efficacy in facilitating timely, reliable, and highly scalable IFF operations in modern combat scenarios.

Fields of Study & Subjects

Blockchain Technology Applications and Security Blockchain Technology in Education and Learning Military Technology and Strategies

Publication details

Journal / source
The Journal of Defense Modeling and Simulation Applications Methodology Technology
Publication date
28 January 2026
Language
EN