Detection of Stealthy Adversaries for Networked Unmanned Aerial Vehicles*
This addresses security vulnerabilities in UAV networks for military or surveillance applications, but it is incremental as it builds on existing model-based detection methods.
The paper tackled the problem of stealthy cyber intrusions disrupting networked UAV operations by developing centralized and decentralized observer techniques for detecting zero-dynamics and covert attacks in formation control settings, with experimental results demonstrating their effectiveness.
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.