An Immune-Knowledge-Driven SCADA-Based Industrial Virus Propagation Model

Junjiang He, Yaxin Li, Jiahang Tang, Hongxia Wang, Geying Yang, Tao Li, Xiaolong Lan

Abstract: Supervisory control and data acquisition (SCADA) systems are the core of industrial control systems and an important part of critical infrastructure. With the deployment of 5G networks around the world, SCADA systems are no longer a relatively secure and physically isolated system like in the past, but are facing huge network virus threats. In order to solve the problem that existing models ignore the communication between nodes in the system, we propose an industrial virus transmission model SELBR based on immune knowledge by simulating the function of T cells in the immune system. By introducing E node, the model is used to realize the function of information transfer between nodes. What is more, we fit the numerical simulation results with the actual data set to verify the existence of the model, and verify the effectiveness of the model for controlling the spread of industrial viruses through model comparison experiments. Numerical results show that the model can effectively control the spread of the virus. Finally, on the basis of parameter sensitivity analysis, preventive suggestions are put forward to further strengthen the security of SCADA system.