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A Survey on Security of UAV Swarm Networks: Attacks and Countermeasures

Published: 22 November 2024 Publication History

Abstract

The increasing popularity of Unmanned Aerial Vehicle (UAV) swarms is attributed to their ability to generate substantial returns for various industries at a low cost. Additionally, in the future landscape of wireless networks, UAV swarms can serve as airborne base stations, alleviating the scarcity of communication resources. However, UAV swarm networks are vulnerable to various security threats that attackers can exploit with unpredictable consequences. Against this background, this article provides a comprehensive review on security of UAV swarm networks. We begin by briefly introducing the dominant UAV swarm technologies, followed by their civilian and military applications. We then present and categorize various potential attacks that UAV swarm networks may encounter, such as denial-of-service attacks, man-in-the-middle attacks, and attacks against Machine Learning (ML) models. After that, we introduce security technologies that can be utilized to address these attacks, including cryptography, physical layer security techniques, blockchain, ML, and intrusion detection. Additionally, we investigate and summarize mitigation strategies addressing different security threats in UAV swarm networks. Finally, some research directions and challenges are discussed.

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cover image ACM Computing Surveys
ACM Computing Surveys  Volume 57, Issue 3
March 2025
984 pages
EISSN:1557-7341
DOI:10.1145/3697147
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 November 2024
Online AM: 08 November 2024
Accepted: 03 November 2024
Revised: 08 September 2024
Received: 13 December 2023
Published in CSUR Volume 57, Issue 3

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  1. UAV swarm networks
  2. security technologies
  3. network attacks
  4. security countermeasures

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  • Natural Science Foundation of China
  • National Natural Science Foundation of Chongqing
  • Science and Technology Research Program for Chongqing Municipal Education Commission
  • Hong Kong RGC Research Impact Fund
  • Collaborative Research Fund

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