论文标题
检测网络无人机的隐形对手**
Detection of Stealthy Adversaries for Networked Unmanned Aerial Vehicles*
论文作者
论文摘要
无人驾驶汽车（UAV）网络在执行复杂的合作任务时提供了分布式覆盖，可重新配置和可操作性。但是，它取决于无线通信，这些通信可能容易受到网络对手和入侵的影响，从而破坏了整个网络的操作。本文开发了基于模型的集中和分散的观察者技术，用于检测一类隐秘的入侵，即零动力和秘密攻击，对编队控制设置中的网络无人机进行了秘密攻击。在控制中心中运行的集中观察者利用无人机的通信拓扑检测进行切换，而分散的观察者在网络中的每个无人机上实现了分散的观察者，使用网络无人机的模型和本地可用的测量。提供实验结果以显示在不同案例研究中提出的检测方案的有效性。
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.
