Abstract:

AAiming at the current situation that the deployment of a large number of information security devices still relies on manual deployment, this paper proposed an information security device deployment guarantee technology based on machine learning algorithms.On the basis of in-depth study of the existing information security equipment deployment guarantee scheme, all the attribute characteristics of the equipment allocation in the scheme were analyzed. The equipment deployment guarantee sample set was constructed according to the existing information security equipment deployment guarantee scheme and the extracted attribute features. The forest algorithm optimized the attribute features and the most reasonable attribute features were selected. Combined with the support vector machine algorithm, the allocation guarantee model was constructed. The experimental comparison showed that the accuracy of the model test set with the random forest algorithm increased by nearly 8%, and the model running time was reduced by 43%. In the process of solving the actual problem, the error rate of the original plan was 8.69%.

Key words: information security equipment, deployment support technology, deployment scheme, random forest, support vector machine, predicted model