Network Security Situation Awareness Model and Empirical Re-search Based on Artificial Intelligence

With the advancement of technology iteration, the trend of industrial automation is becoming more and more prominent, and the era of Industry 4.0, which is dominated by intelligent manufacturing, is coming. The industrial internet is booming. However, due to the increasing complexity of the network environment and various types of cyber attacks, there are huge challenges for the industrial internet. Traditional network security devices adopt isolated protection measures and cannot achieve information sharing, which can only reflect the security of the network from one side. Therefore, a comprehensive evaluation of the current security status of the industrial internet and a prediction of its safety development trend over a certain period are the important directions for the development of industrial internet security. In response to the above issues, this paper proposes to improve the traditional Particle Swarm Optimization (PSO) algorithm and combine it with Long Short-Term Memory Network (LSTM) to carry out security situation risk assessment. To provide network managers with more valuable network security situation information.