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

• URL: http://arxiv.org/abs/2605.26876v1
• Date: Tue, 26 May 2026 11:33:02 GMT
• Title: Secure UAV Swarms in Low-Altitude Wireless Networks: Challenges and Solutions
• Abstract summary: This paper proposes a cloud-edge-end collaborative defense framework for UAV swarms.<n>First, a cooperative perception scheme is designed to resist GPS spoofing.<n>Second, a behavior-driven authentication method with trust evaluation is developed to mitigate insider threats.<n>Third, a multi-agent attack forensics framework is devised to intelligently trace the propagation paths of multi-hop attacks in UAV networks.
• Score: 28.36153282686918
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

Related papers

• LLM-Centric Agentic AI for UAV Swarms: Architecture, Enabling Technologies, and Open Problems [4.4579151410787246]
  Uncrewed Aerial Vehicle (UAV) swarms have significant potential for applications such as Search and Rescue (SAR) and environmental monitoring.<n>Agentic Artificial Intelligence (AI) represents a shift from standalone Large Language Model (LLM) toward closed-loop cognitive architectures.<n>This paper proposes LLM-Centric Agentic AI for UAV Swarms (LAUS) and reviews key enabling technologies.
  arXiv  Detail & Related papers  (2026-07-05T13:08:06Z)
• AI-driven Intrusion Detection for UAV in Smart Urban Ecosystems: A Comprehensive Survey [3.26654570054705]
  This paper provides a structured, evidence-based synthesis of UAV applications in smart cities and their associated security challenges.<n>We categorize these challenges into two primary classes: 1) cyber-attacks targeting the communication infrastructure of UAVs and 2) unwanted or unauthorized physical intrusions by UAVs themselves.<n>We analyze how AI-based methods, such as machine/deep learning for anomaly detection and computer vision for object recognition, can play a pivotal role in enhancing UAV security.
  arXiv  Detail & Related papers  (2026-01-27T08:26:05Z)
• ORCA -- An Automated Threat Analysis Pipeline for O-RAN Continuous Development [57.61878484176942]
  Open-Radio Access Network (O-RAN) integrates numerous software components in a cloud-like deployment, opening the radio access network to previously unconsidered security threats.<n>Current vulnerability assessment practices often rely on manual, labor-intensive, and subjective investigations, leading to inconsistencies in the threat analysis.<n>We propose an automated pipeline that leverages Natural Language Processing (NLP) to minimize human intervention and associated biases.
  arXiv  Detail & Related papers  (2026-01-20T07:31:59Z)
• Multi-Agent-Driven Cognitive Secure Communications in Satellite-Terrestrial Networks [58.70163955407538]
  Malicious eavesdroppers pose a serious threat to private information via satellite-terrestrial networks (STNs)<n>We propose a cognitive secure communication framework driven by multiple agents that coordinates spectrum scheduling and protection through real-time sensing.<n>We exploit generative adversarial networks to produce adversarial matrices, and employ learning-aided power control to set real and adversarial signal powers for protection layer.
  arXiv  Detail & Related papers  (2026-01-06T10:30:41Z)
• When UAV Swarm Meets IRS: Collaborative Secure Communications in Low-altitude Wireless Networks [68.45202147860537]
  Low-altitude wireless networks (LAWNs) provide enhanced coverage, reliability, and throughput for diverse applications.<n>These networks face significant security vulnerabilities from both known and potential unknown eavesdroppers.<n>We propose a novel secure communication framework for LAWNs where the selected UAVs within a swarm function as a virtual antenna array.
  arXiv  Detail & Related papers  (2025-10-25T02:02:14Z)
• From Static to Adaptive Defense: Federated Multi-Agent Deep Reinforcement Learning-Driven Moving Target Defense Against DoS Attacks in UAV Swarm Networks [23.908450903174725]
  We propose a novel framework for proactive DoS mitigation in UAV swarms.<n>We design lightweight and coordinated MTD mechanisms, including leader switching, route mutation, and frequency hopping.<n>Our approach significantly outperforms state-of-the-art baselines.
  arXiv  Detail & Related papers  (2025-06-09T03:33:04Z)
• An LLM-based Self-Evolving Security Framework for 6G Space-Air-Ground Integrated Networks [49.605335601285496]
  6G space-air-ground integrated networks (SAGINs) offer ubiquitous coverage for various mobile applications.<n>We propose a novel security framework for SAGINs based on Large Language Models (LLMs)<n>Our framework produces highly accurate security strategies that remain robust against a variety of unknown attacks.
  arXiv  Detail & Related papers  (2025-05-06T04:14:13Z)
• Secure Physical Layer Communications for Low-Altitude Economy Networking: A Survey [76.36166980302478]
  The Low-Altitude Economy Networking (LAENet) is emerging as a transformative paradigm.<n>Physical layer communications in the LAENet face growing security threats due to inherent characteristics of aerial communication environments.<n>This survey comprehensively reviews existing secure countermeasures for physical layer communication in the LAENet.
  arXiv  Detail & Related papers  (2025-04-12T09:36:53Z)
• Toward Mixture-of-Experts Enabled Trustworthy Semantic Communication for 6G Networks [82.3753728955968]
  We introduce a novel Mixture-of-Experts (MoE)-based SemCom system. This system comprises a gating network and multiple experts, each specializing in different security challenges. The gating network adaptively selects suitable experts to counter heterogeneous attacks based on user-defined security requirements. A case study in vehicular networks demonstrates the efficacy of the MoE-based SemCom system.
  arXiv  Detail & Related papers  (2024-09-24T03:17:51Z)
• A Survey of Security in UAVs and FANETs: Issues, Threats, Analysis of Attacks, and Solutions [1.0923877073891446]
  It is critical that security is ensured for UAVs and the networks that provide communication between UAVs. This survey seeks to provide a comprehensive perspective on security within the domain of UAVs and Flying Ad Hoc Networks (FANETs)
  arXiv  Detail & Related papers  (2023-06-25T16:15:40Z)
• Dynamic Radar Network of UAVs: A Joint Navigation and Tracking Approach [36.587096293618366]
  An emerging problem is to track unauthorized small unmanned aerial vehicles (UAVs) hiding behind buildings. This paper proposes the idea of a dynamic radar network of UAVs for real-time and high-accuracy tracking of malicious targets.
  arXiv  Detail & Related papers  (2020-01-13T23:23:09Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.