Introduction - If you have any usage issues, please Google them yourself
As the basis of the whole network security situation awareness, the quality of situation elements extraction will directly affect the performance of the situation awareness system. To solve the problem that the situation element is difficult to extract, we propose a method to extract the hierarchical frame situation elements based on the enhanced probabilistic neural network. In the hierarchical access frame, we use the principal component analysis (PCA) to reduct the training sample attribute and to process the special attribute encoding fusion. The result can be used to optimize the structure of the probabilistic neural network (PNN) and reduce the system complexity. Take PNN as the base classifier to form the final strong classifier by repeated iteration, weight replacement and weighted fusion. The experimental results show that the scheme is an effective method to obtain the situation factors and its accuracy is 95.53%,which is significantly better than other algorithms.