面向网络化无人机的隐蔽对手检测*
Detection of Stealthy Adversaries for Networked Unmanned Aerial Vehicles*
AI总结：
本文针对网络化无人机编队控制中的零动态和隐蔽攻击，提出集中式与分散式观测器检测方法，利用通信拓扑切换和本地测量实现隐蔽入侵检测，并通过实验验证其有效性。
摘要：
无人机网络在执行复杂协同任务时能够提供分布式覆盖、可重构性和机动性。然而，它依赖的无线通信可能容易受到网络对手和入侵的影响，从而破坏整个网络的运行。本文开发了基于模型的集中式和分散式观测器技术，用于在编队控制场景下检测网络化无人机上的一类隐蔽入侵，即零动态攻击和隐蔽攻击。运行在控制中心的集中式观测器利用无人机通信拓扑的切换进行攻击检测，而部署在网络中每架无人机上的分散式观测器则使用网络化无人机模型和本地可用的测量信息。实验结果表明，所提出的检测方案在不同案例研究中具有有效性。
英文摘要：
A network of unmanned aerial vehicles (UAVs) provides distributed coverage, reconfigurability, and maneuverability in performing complex cooperative tasks. However, it relies on wireless communications that can be susceptible to cyber adversaries and intrusions, disrupting the entire network's operation. This paper develops model-based centralized and decentralized observer techniques for detecting a class of stealthy intrusions, namely zero-dynamics and covert attacks, on networked UAVs in formation control settings. The centralized observer that runs in a control center leverages switching in the UAVs' communication topology for attack detection, and the decentralized observers, implemented onboard each UAV in the network, use the model of networked UAVs and locally available measurements. Experimental results are provided to show the effectiveness of the proposed detection schemes in different case studies.
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。
