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A resilient distributed algorithm is proposed to solve the distributedresource allocation problem of a first-order nonlinear multi-agent system whois subject to false data injection (FDI) attacks. An intelligent attackerinjects false data into agents' actuators and sensors such that agents executethe algorithm according to the compromised control inputs and interactiveinformation. The goal of the attacker is to make the multi-agent system to beunstable and to cause the deviance of agents' decisions from the optimalresource allocation. At first, we analyze the robustness of a distributedresource allocation algorithm under FDI attacks. Then, the unknown nonlinearterm and the false data injected in agents are considered as extended stateswhich can be estimated by extended state observers. The estimation was used inthe feedback control to suppress the effect of the FDI attacks. A resilientdistributed resource allocation algorithm based on the extended state observeris proposed to ensure that it can converge to the optimal allocation withoutrequiring any information about the nature of the attacker. An example is givento illustrate the results.

Resilient distributed resource allocation algorithm under false data injection attacks