Cyberattack Detection in Multi-Agent System

In this paper, we investigate the secure consensus problem for multiple-input-multiple-output (MIMO) linear multi-agent systems (MASs) under false data injection (FDI) attacks, where an adversary corrupts the output measurements exchanged among agents. To mitigate the effect of such attacks, we design an unknown input observer (UIO) that relies only on relative output information and reconstructs the consensus error while filtering out the injected malicious signals. On the basis of the proposed observer, we design a robust consensus control law. By employing a common Lyapunov function (CLF) together with linear matrix inequality (LMI) techniques, we establish sufficient stability conditions ensuring that consensus among agents is preserved even when false data injection (FDI) attacks occur, provided certain observability and robustness conditions are met.