Simulation of Intrusion Response Model for Industrial Control Network Based on Fuzzy Clustering Algorithm

In order to respond more effectively to the increasingly complex network security threats, in order to improve the network security of industrial control systems, and to provide a more powerful network defense mechanism for industrial control systems. In this paper, an industrial control network intrusion response model is designed based on the fuzzy clustering algorithm. Firstly, by generalizing the intrusion feature set with a certain degree of similarity, the intrusion feature library matrix is established after standardization. Then, categorizing the set of intrusion features, creating a fuzzy matrix to determine the similarity between the matrices, and realizing the overall framework construction of the model according to the conditions of intrusion response determination, the design of industrial control network intrusion response model based on fuzzy clustering algorithm is completed. Through simulation, the risk factor of portscan attack reaches 0.830, which is higher than the threshold value of 0.4. At $12 \mathrm{~s}-20 \mathrm{~s}$, along with the increasing intensity of the attack, the network traffic and CPU utilization are increasing. The validation shows that the fuzzy algorithm successfully reduces the network traffic and decreases the CPU utilization.