PrivLLMSwarm: 用于安全物联网监控的隐私保护大语言模型驱动的无人机群
PrivLLMSwarm: Privacy-Preserving LLM-Driven UAV Swarms for Secure IoT Surveillance
AI总结：
PrivLLMSwarm通过安全多方计算实现隐私保护的大语言模型驱动无人机群，实现高准确性和低延迟的加密推理，适用于隐私敏感的物联网应用。
摘要：
大语言模型（LLMs）正逐渐成为在物联网（IoT）环境中运行的无人 aerial 载具（UAV）群进行自主推理和自然语言协调的强大赋能者。然而，现有的LLM驱动的UAV系统以明文处理敏感的操作数据，暴露于隐私和安全风险中。本工作引入了PrivLLMSwarm，一个隐私保护框架，通过安全多方计算（MPC）在UAV群协调中执行安全的LLM推理。该框架集成了MPC优化的transformer组件，并通过非线性激活的高效近似，使在资源受限的空中平台上实现加密推理成为可能。通过模拟中的强化学习进行微调的基于GPT的命令生成器，提供了可靠指令的同时保持保密性。在城市规模的模拟实验中证明，PrivLLMSwarm实现了高语义准确性、低加密推理延迟以及在隐私约束下的稳健编队控制。比较分析显示，PrivLLMSwarm相比差分隐私、联邦学习和明文基线在隐私-效用平衡方面更具优势。为了支持可重复性，完整的实现包括源代码、MPC组件和合成数据集已公开可用。PrivLLMSwarm为隐私敏感的物联网应用中安全、LLM驱动的UAV群建立了实用基础，包括智能城市监控和应急响应。
英文摘要：
Large Language Models (LLMs) are emerging as powerful enablers for autonomous reasoning and natural-language coordination in unmanned aerial vehicle (UAV) swarms operating within Internet of Things (IoT) environments. However, existing LLM-driven UAV systems process sensitive operational data in plaintext, exposing them to privacy and security risks. This work introduces PrivLLMSwarm, a privacy-preserving framework that performs secure LLM inference for UAV swarm coordination through Secure Multi-Party Computation (MPC). The framework incorporates MPC-optimized transformer components with efficient approximations of nonlinear activations, enabling practical encrypted inference on resource-constrained aerial platforms. A fine-tuned GPT-based command generator, enhanced through reinforcement learning in simulation, provides reliable instructions while maintaining confidentiality. Experimental evaluation in urban-scale simulations demonstrates that PrivLLMSwarm achieves high semantic accuracy, low encrypted inference latency, and robust formation control under privacy constraints. Comparative analysis shows PrivLLMSwarm offers a superior privacy-utility balance compared to differential privacy, federated learning, and plaintext baselines. To support reproducibility, the full implementation including source code, MPC components, and a synthetic dataset is publicly available. PrivLLMSwarm establishes a practical foundation for secure, LLM-enabled UAV swarms in privacy-sensitive IoT applications including smart-city monitoring and emergency response.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
