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

2026-05-26

AI Summary

This study addresses the critical security challenges faced by low-altitude unmanned aerial vehicle (UAV) swarms operating in open, dynamic environments, where they are vulnerable to GPS spoofing, insider threats, and multi-hop intrusions, further compounded by stringent onboard resource constraints, time-varying network topologies, and intelligent adversaries. To tackle these issues, this work proposes the first cloud–edge–device collaborative security defense framework tailored for such scenarios, integrating interactive attack–defense game-theoretic modeling, behavior-driven trust-based authentication, and multi-agent attack traceback techniques. Experimental results demonstrate that the proposed approach effectively mitigates GPS spoofing attacks, accurately identifies malicious nodes, and precisely traces multi-hop attack paths, thereby significantly enhancing the cybersecurity resilience of UAV swarms.

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 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.

Problem

• UAV swarms
• security risks
• GPS spoofing
• insider threats
• multi-hop intrusion

Innovation

• UAV swarms
• cloud-edge-end collaboration
• GPS spoofing defense
• behavior-driven authentication
• multi-agent attack forensics