Research on Situational Awareness of Network Security Based on Machine Learning

The existing information security situation awareness technology mostly uses RBF (RBF) radiation basis functions to extract information, which is susceptible to changes in the time domain threshold of attacks, resulting in low accuracy in information security situation identification. Therefore, this project proposes a new information security situational awareness algorithm for big data. The research content includes: extracting information security information elements from information systems, establishing a cognitive model of information security information environment information using machine learning methods, and achieving information security situational awareness. The research results of this project will provide new ideas for network security situational awareness, and provide theoretical basis for improving the overall transmission performance of the network and reducing network security risks.