Detection of Stealthy Adversaries for Networked Unmanned Aerial Vehicles
Detection of Stealthy Adversaries for Networked Unmanned Aerial Vehicles
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DOI：
10.1109/icuas54217.2022.9836208
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发表时间：
2022-02
期刊：
影响因子：
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通讯作者：
Mohammad Bahrami;H. Jafarnejadsani
中科院分区：
文献类型：
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作者：
Mohammad Bahrami;H. Jafarnejadsani
无人机（UAV）网络提供分布式覆盖，可重构性和机动性，以执行复杂的合作任务。然而，它依赖于无线通信，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，用于检测编队控制环境中联网无人机的一类隐形入侵，即零动态和隐蔽攻击。在控制中心运行的集中式观测器利用UAV的通信拓扑中的切换来进行攻击检测，并且在网络中的每个UAV上实现的分散式观测器使用联网UAV的模型和本地可用的测量。实验结果表明，在不同的情况下，所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.