Information Security Detection Technology for Industrial Control Equipment Modeling Generated by Excitation Traversal Test Based on Big Data

The paper results from the “Information Security Inspection of Rail Transit Industrial Control System” Development and Reform Office High-Tech [2012] No. 1424 Project initiated by the National Development and Reform Commission. This paper constructs a cloud-edge-terminal architecture for the full life cycle control of industrial control systems based on brain-like computing, and puts forward a new method for security guarantee of rail transit industrial control network and big data detection method. First of all, the excites vibration input test of external physical quantity is carried out according to the operation manual of physical equipment. The corresponding frequency spectrum relationship (based on the occurrence frequency of function of time series) is generated in specific applications according to equipment functions, and the function simulation is carried out. The obtained discrete physical quantity data of the test input/output sequence is generated according to a specific time-space relationship and operation flow. The data are stored in an exponentially large data tablespace elastically, which can be searched and used in sequence according to the time-space parameters subsequently. Among them, the data generated by each function point should be firstly processed by Kalman filtering and then characterized by AI to extract the behavior mode of function input/output. Through this method, the operation principle of equipment function (behavior) can be perspective simulated, and the security operation guarantee system of industrial control equipment based on operation flow is constructed to ensure the security operation of industrial control equipment.