关键词: 网络态势预测, 信息安全, 粒子群优化算法, 支持向量机, 神经网络

Abstract: Network security has become particularly important in today's high-speed life. Network security situation prediction can predict the trend of the network situation effectively. By analyzing the advantages and disadvantages of existing regression analysis prediction models and neural network-based prediction models, a new data analysis model was explored. The particle swarm optimization algorithm was applied to the parameter selection process of support vector machine. The prediction model and framework were constructed according to the characteristics of the data sample base, so the prediction performance and accuracy are improved. Compared with the network situation prediction method based on neural network, the experiment shows that the model has better situation prediction performance, higher prediction accuracy and faster forecasting speed. It can help managers to predict the network situation in time and maintain the security and stability of the network.

Key words: network situation prediction, information security, particle swarm optimization, SVR, neural network