mlsanityData to 14 Oct 2026

Large AI Model-Enabled Secure Communications in Low-Altitude Wireless Networks: Concepts, Perspectives and Case Study

arXiv 2508.00256 ↗First posted 1 Aug 2025cs.NI cs.AIcited by 0

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Abstract (arXiv)

Low-altitude wireless networks (LAWNs) have the potential to revolutionize communications by supporting a range of applications, including urban parcel delivery, aerial inspections and air taxis. However, compared with traditional wireless networks, LAWNs face unique security challenges due to low-altitude operations, frequent mobility and reliance on unlicensed spectrum, making it more vulnerable to some malicious attacks. In this paper, we investigate some large artificial intelligence model (LAM)-enabled solutions for secure communications in LAWNs. Specifically, we first explore the amplified security risks and important limitations of traditional AI methods in LAWNs. Then, we introduce the basic concepts of LAMs and delve into the role of LAMs in addressing these challenges. To demonstrate the practical benefits of LAMs for secure communications in LAWNs, we propose a novel LAM-based optimization framework that leverages large language models (LLMs) to generate enhanced state features on top of handcrafted representations, and to design intrinsic rewards accordingly, thereby improving reinforcement learning performance for secure communication tasks. Through a typical case study, simulation results validate the effectiveness of the proposed framework. Finally, we outline future directions for integrating LAMs into secure LAWN applications.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 22 references that are in the map. First posted on arXiv 1 Aug 2025.

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11 of 22 references.

References · 11

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020A Survey on Visual Transformercited by 654
  3. 2024LLM4CP: Adapting Large Language Models for Channel Predictioncited by 42
  4. 2024Large Wireless Model (LWM): A Foundation Model for Wireless Channelscited by 40
  5. 2025WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communicationcited by 40
  6. 2025Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directionscited by 11
  7. 2025From Ground to Sky: Architectures, Applications, and Challenges Shaping Low-Altitude Wireless Networkscited by 8
  8. 2025Secure Physical Layer Communications for Low-Altitude Economy Networking: A Surveycited by 4
  9. 2024Semantic Steganography: A Framework for Robust and High-Capacity Information Hiding using Large Language Modelscited by 3
  10. 2025Terahertz Integrated Sensing and Communication-Empowered UAVs in 6G: A Transceiver Design Perspectivecited by 3
  11. 2025Securing the Sky: Integrated Satellite-UAV Physical Layer Security for Low-Altitude Wireless Networkscited by 2

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  1. 2025When UAV Swarm Meets IRS: Collaborative Secure Communications in Low-altitude Wireless Networks
  2. 2026Agentic AI Networking for Heterogeneous Unmanned Aerial Systems in Low-Altitude Wireless Networks
  3. 2026Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization
  4. 2026Integrated Sensing and Covert Communication In Low-Altitude Networks: A Smart Radio Environment Perspective ↗
  5. 2025Large Language Model-enhanced Reinforcement Learning for Low-Altitude Economy Networking
  6. 2024Multi-objective Aerial Collaborative Secure Communication Optimization via Generative Diffusion Model-enabled Deep Reinforcement Learning
  7. 2025AI-Driven Low-Altitude Economy: Spectrum, Mobility, and Validation
  8. 2026Multi-Agent Collaborative Intrusion Detection for Low-Altitude Economy IoT: An LLM-Enhanced Agentic AI Framework