Research on the Evaluation Model of Key Indicators of Power Internet Health Status

In order to solve the problem of large identification errors in traditional attack information identification methods, a machine learning-based power Internet attack information identification method is proposed. The research of this project is to evaluate the key indicators of the health of the power Internet business, such as infrastructure (cpu, memory), data operation status during business operation or the operation status of the full link of the business, etc. Evaluation. Based on this system, the test environment is built as an implementation case, and the health status of the communication network equipment, network and business can be obtained through health examination and online diagnostic analysis to assist the operation and maintenance personnel to fully grasp the operation status of the communication network. In this paper, through the collection of internal and external data of electric power, through intelligent information fusion and other technologies, to realize data cross-border fusion, and tap the potential value of electric power big data. Through data analysis and cross-border integration, a comprehensive management platform for cross-border big data based on power security is built.