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TRIBES: Twin-driven Resilient and Intelligent Blockchain-enabled Security Framework for UAV Swarms

  • Narzullo Khodjamov
  • , Song Yang*
  • , Buyu Wang
  • , Yanan Gao
  • , Fan Li
  • , Sardor Mamarasulov
  • , Jingwei Qi
  • , Liehuang Zhu
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • Inner Mongolia Agricultural University
  • Samarkand State University

Research output: Contribution to journalArticlepeer-review

Abstract

Unmanned Aerial Vehicle (UAV) swarms operating in contested environments must achieve secure coordination, perform real-time fault detection and containment, and enforce operational policies under conditions of dynamic membership and hostile interference. However, existing approaches remain limited to addressing singular and specific issues, failing to provide a comprehensive, unified system security framework. We present TRIBES, a modular four-layer trust framework that unifies distributed consensus, online anomaly detection with the Digital Twin (DT) technique, privacy-preserving attestation, and resilient dual-path communications without centralized infrastructure. The architecture anchors a lightweight Directed Acyclic Graph (DAG) ledger with a reconfigurable Practical Byzantine Fault Tolerance (PBFT) committee, achieving sub-second finality in typical operation. Simulation studies with realistic swarm dynamics under spoofing, jamming, and Sybil attacks demonstrate that TRIBES sustains auditable trust decisions with low tail latency, while DTs detect compromised behavior with high accuracy and few false alarms. Privacy is preserved through differential perturbation and simulated zero-knowledge attestations, enabling on-chain enforcement of geofencing and other operational policies. Compared with decentralized baselines, TRIBES reduces worst-case consensus latency by about one-third and maintains swarm coordination even under targeted disruption.

Original languageEnglish
Article number116189
JournalKnowledge-Based Systems
Volume347
DOIs
Publication statusPublished - 19 Jul 2026
Externally publishedYes

Keywords

  • Anomaly detection
  • Blockchain consensus
  • Digital Twins
  • Privacy
  • UAV swarms

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