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Secure UAV Swarms in Low-Altitude Wireless Networks: Challenges and Solutions

arXiv Security Archived May 27, 2026 ✓ Full text saved

arXiv:2605.26876v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) swarms are increasingly deployed in vast low-altitude applications, owing to their capabilities in distributed sensing, flexible communication, and autonomous coordination. Nevertheless, the open and highly dynamic operating environment of UAV swarms introduces serious security risks, including GPS spoofing, insider threats, and multi-hop intrusion. These threats are aggravated by limited on-board resources, frequently

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    Computer Science > Cryptography and Security [Submitted on 26 May 2026] Secure UAV Swarms in Low-Altitude Wireless Networks: Challenges and Solutions Yuntao Wang, Haojia Yang, Han Liu, Jianle Ba, Zhou Su Unmanned aerial vehicle (UAV) swarms are increasingly deployed in vast low-altitude applications, owing to their capabilities in distributed sensing, flexible communication, and autonomous coordination. Nevertheless, the open and highly dynamic operating environment of UAV swarms introduces serious security risks, including GPS spoofing, insider threats, and multi-hop intrusion. These threats are aggravated by limited on-board resources, frequently changing network topology, and the presence of intelligent adversaries. To tackle these issues, this paper proposes a cloud-edge-end collaborative defense framework for UAV swarms. Based on this framework, three complementary mechanisms are developed. First, a cooperative perception scheme is designed to resist GPS spoofing via interactive attack-defense game modeling. Second, a behavior-driven authentication method with trust evaluation is developed to mitigate insider threats. Third, a multi-agent attack forensics framework is devised to intelligently trace the propagation paths of multi-hop attacks in UAV networks. Experimental results validate the effectiveness of the proposed approaches. Finally, several open research directions are outlined. Comments: 7 pages, 6 figures Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2605.26876 [cs.CR]   (or arXiv:2605.26876v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.26876 Focus to learn more Submission history From: Yuntao Wang [view email] [v1] Tue, 26 May 2026 11:33:02 UTC (1,500 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
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    ◬ AI & Machine Learning
    Published
    May 27, 2026
    Archived
    May 27, 2026
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