Cyber Security Situation Prediction Model Based on GWO-SVM

Human life and work are inseparable from information technology, and the cyber security issues that follow have become increasingly severe. In order to predict the development trend of cyber safety more accurately, this paper establishes a kind of network safety situation forecast model based on Grey Wolf Optimization (GWO) algorithm to optimize support vector machine (SVM) parameters, and solves the problem of support vector machine (SVM) parameter optimization. It overcomes the problems of neural network training and local optimization, which makes it more generalized, also effectively improve the prediction effect of SVM. The simulation experiments indicate that this model has improved the accuracy of prediction and shows the general tendency of the network security situation.

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