Abstract:Network security has become a priority research field in China in recent years, for there would be no national security without network security. In consideration of the characteristics of data source in network security like diversity and complexity, this study proposes an evaluation model of network security situation based on Support Vector Machine (SVM) and self-adaptive weight. The model is composed of training module and prediction module. The training module is used to obtain the key data concerned by network security through prior knowledge method and build evaluation model with a combination of SVM and weight strategy. The prediction module is used for real-time network security situation evaluation. Analysis of experimental process and results indicates that the proposed model can favorably support the real-time prediction and evaluation of the security situation of small-size networks.