A Microgrid Controller Security Monitoring Model Based On Message Flow

With the development of computer technology, information technology, big data, artificial intelligence, and industrial automation technology, information technology has been widely used in the field of industrial control. However, microgrid terminals generally work in an open environment and have the computing power and wireless communication functions, making them more vulnerable to attacks and threatening the security of the power grid. This paper proposes a method of using message flow to build a safety monitoring model and evaluates it through experiments. We use the external characteristics of network traffic flow to generate the model, that is, the specific content of network traffic is not considered. We validate that it is feasible to detect attacks with a detection accuracy above 95% by using machine learning methods.