An SSUT network security situation awareness method based on supporting extended index system is proposed

it is to solve the problems that the current index system of network security situation awareness is lack of extendibility and unified norms

can not to meet the practice application environment and the personalized demand which cause the awareness result is not accurate enough. The traditional network security index system is reclassified and quantified in this method

which support for extending the common or new index. The Support Vector Machine is adopted as the classification method to evaluate and analyze the network security situation. Its proved through the simulation experiment results that the classification accuracy is increased about 15.4%~16.67% by the SSUT model than the traditional model

and the accuracy of the network security situation awareness is enhanced effectively.