A Privacy-Aware Task Distribution Architecture for UAV Communications System Using Blockchain

Chengzu DONG, Shantanu PAL, Shiping CHEN, Frank JIANG, Xiao LIU

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

Unmanned Aerial Vehicles (UAVs) have witnessed significant growth in various domains, such as agriculture, disaster management, and remote health management systems. However, the use of UAVs necessitates secure and efficient solutions that uphold privacy during task distribution. To address this challenge, this paper introduces a novel architecture for privacy-aware task distribution in UAV communication systems. Our approach leverages the benefits of blockchain and smart token-based identification within the proposed architecture, ensuring decentralized, transparent, and tamper-proof operations. By adopting a crowdsourced task distribution model, our approach further optimizes task assignment among UAVs while prioritizing data privacy, user access control, and scalability. The architecture is designed to enhance fault tolerance, enabling seamless operation under dynamic and unpredictable conditions. We present a comprehensive implementation details of a proof-of-concept prototype of our proposed architecture, detailing its design and functionality. The experimental results demonstrate the feasibility, efficiency, and adaptability of our approach in diverse real-world scenarios, highlighting its potential for broader adoption across UAV applications.
Original languageEnglish
JournalIEEE Internet of Things Journal
Early online date16 Jan 2025
DOIs
Publication statusE-pub ahead of print - 16 Jan 2025

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Aerial Computing
  • Blockchain
  • Internet of Things
  • Privacy
  • Task Distribution
  • Unmanned Aerial Vehicles

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