Research on Risk Warning Technology of IT Equipment based on Machine Learning

IT equipment regulatory agencies have accumulated a large amount of data in the process of supervision and inspection. In order to fully tap the potential value, enhance supervision pertinence, improve inspection efficiency, apply and optimize data mining technologies such as association rule mining, community discovery, and visualization. We need to build a macro security risk early warning method based on machine learning algorithms. The research found that the IT equipment supervision system built in this paper achieves the purpose of machine identification instead of manual screening, which can greatly reduce the workload of IT equipment management and improve the timeliness and accuracy of risk research and judgment.