基于TWSVM的C4ISR网络安全态势评估方法

Assessment Model of Command Information System Security Situation Based on Twin Support Vector Machines

为进一步提升基于SVM的C4ISR网络安全态势评估方法的评估精度和鲁棒性,提出了一种基于孪生支持向量机的C4ISR网络安全态势评估方法。该方法首先分析了影响C4ISR网络安全态势的主要因素,然后基于孪生支持向量机,建立了C4ISR网络安全态势评估模型,通过非线性映射将网络安全态势样本各个要素特征向量映射到高维特征空间,继而利用多类核函数构造的不同分类面以及分类函数来对网络安全态势样本数据进行学习和参数估计,从而得到全局最优分类解。实验结果表明,与基于SVM的网络安全态势评估方法相比,所提方法在提高评估正确率的同时能够动态高效地反映出当前网络的安全态势,具有较强的鲁棒性。

In order to further improve the evaluation accuracy and robustness of C4ISR networksecurity situation assessment method based on SVM,a security assessment method of C4ISR networkbased on twin support vector machines is proposed in this paper. This method firstly analyzes the mainfactors influencing the security situation of C4ISR network,and then C4ISR network security situationevaluation model based on twin support vector matrix is boiled. The non-linear mapping maps eachfeature eigenvector of the network security situation sample to high dimensional feature space,then usethe different classification surfaces constructed by multi-class kernel function and classificationfunction to study the network security situation sample data and estimate the parameters,so as to getthe global optimal classification solution. The experimental results show that compared with SVM-basednetwork security situation assessment method,the proposed method can improve the evaluation accuracyand dynamically reflect the current network security situation,and has strong robustness.