灰色关联分析与支持向量机相融合的网络安全态势评价

Evaluation of network security situation based on grey relational analysis and support vector machine

为了提高网络安全态势的评价准确性,提出一种灰色关联分析与支持向量机相融合的网络安全态势评价模型。首先采用灰色关联分析对网络安全态势评价指标进行筛选,并根据对评价结果贡献赋予评价指标权值,然后将重要的评价指标作为支持向量机的输入向量,并采用社会力模型算法选择模型的参数,最后采用仿真实例分析了模型的评价性能。实验结果表明,本文模型通过灰色关联分析选择支持向量机的输入向量和社会力模型算法选择了最合理的型参数,可以准确描述网络安全态势与评价指标之间的变化关系,不仅提高了网络安全态势评价的正确率,加快了建模速度,而且获得比经典模更优的评价结果。

In order to improve the evaluation accuracy of network security situation,a evaluation model is proposed based on grey relational analysis combined with support vector machine.First of all,the evaluation index are selected by grey relational analysis and weight are given according to the contribution for the evaluation result,and then the important index are input to support vector machine which parameters are selected by using the social force model algorithm,finally the performance of evaluation model is analyzed by simulation examples.The experimental results show that the proposed model which uses gray correlation analysis to select the input vectors of support vector machine while social force model algorithm chose the type parameters of the most reasonable,can accurate describe change relationship between the network security situation and evaluating index,not only improve the evaluation correct rate of network security situation,but also accelerate the speed,and obtain more better evaluation results than the classical models.