李纪真, 孟相如, 杨栋, 康巧燕. 一种支持扩展指标体系的SSUT网络安全态势评估[J]. 微电子学与计算机, 2015, 32(2): 15-19.
引用本文: 李纪真, 孟相如, 杨栋, 康巧燕. 一种支持扩展指标体系的SSUT网络安全态势评估[J]. 微电子学与计算机, 2015, 32(2): 15-19.
LI Ji-zhen, MENG Xiang-ru, YANG Dong, KANG Qiao-yan. An SSUT Network Security Situation Awareness Method Based on Supporting Extended Index System[J]. Microelectronics & Computer, 2015, 32(2): 15-19.
Citation: LI Ji-zhen, MENG Xiang-ru, YANG Dong, KANG Qiao-yan. An SSUT Network Security Situation Awareness Method Based on Supporting Extended Index System[J]. Microelectronics & Computer, 2015, 32(2): 15-19.

一种支持扩展指标体系的SSUT网络安全态势评估

An SSUT Network Security Situation Awareness Method Based on Supporting Extended Index System

  • 摘要: 提出一种支持扩展指标体系的SSUT网络安全态势评估模型.该模型将传统网络安全指标重新归类和量化,并支持对常见或新指标的扩展,采用支持向量机分类方法实现对网络安全态势的评估与分析.仿真实验结果表明SSUT模型比普通模型分类准确率提高了近15.4%~16.67%,有效提升了网络安全态势评估的准确性.

     

    Abstract: 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. It's 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.

     

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