Abstract
This paper focus on the detection for false data injection (FDI) attacks. Under external conditions, the state and the output variables of Nonlinear Cyber‐Physical Systems (NCPSs) cannot be described by a linear relationship. It is difficult to detect the attacked systems. The Laguerre function model has excellent approximation capability to change structural parameters such as system delay and order, making it convenient for online parameter identification and suitable for complex industrial process control. Accordingly, in order to detect FDI attacks for NCPSs, the Laguerre function is adopted to detect FDI attacks and improve the detection rate. Numerical simulations verify the effectiveness of this method.
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