基于数值模拟的网络安全风险量化参数优化分析

为了解决传统方法无法得到有效参数，导致建立网络安全风险量化模型量化精度低的弊端，通过数值模拟方法研究了网络安全风险量化参数优化问题。针对主机风险计算，依据主机所处状态对风险向量进行定义，通过加权计算得到合理的权重函数，将主机直接风险值和间接风险值结合在一起，获取主机风险值。将主机风险值相加求和，求算数平均值，获取网络在某时刻的平均风险值。针对风险值中的复杂函数，采用引入时延的支持向量机方法建立网络安全风险量化模型，对其进行描述。针对建立的网络安全风险量化模型中的重要参数惩罚因子和核函数宽度系数，采用蚁群算法进行初寻优，对待优化参数进行数值模拟，得到最优惩罚因子为10，最优核函数宽度系数为0.112。结果表明：采用所提方法对网络中主机1进行安全风险量化，得到的结果和主机1实际风险情况相符，研究其它主机可得到相同结论；所提方法对网络安全风险量化值和实际结果最为相符；所提方法量化结果误差最低。可见所提方法参数优化性能优，对网络安全风险量化精度高。

Optimization Analysis of Network Security Risk Quantification Parameters Based on Numerical Simulation

In order to solve the problem that traditional methods can not get effective parameters, which leads to the low accuracy of network security risk quantification model, the optimization of network security risk quantification parameters is studied by numerical simulation method. In view of the host risk calculation, the risk vector is defined according to the host state, and the reasonable weight function is obtained by weighting calculation. The host direct risk value and the indirect risk value are combined to obtain the host risk value. Summing up the sum of the host risk values, calculating the mean value, and obtaining the average risk value of the network at a certain time. Aiming at the complex function in the risk value, a network security risk quantification model is established by introducing delay support vector machine method and described. Aiming at the important parameter penalty factor and kernel function width coefficient in the network security risk quantification model, ant colony algorithm is used to optimize the parameters. The optimal penalty factor is 10 and the optimal kernel function width coefficient is 0.112. The results show that the proposed method can quantify the security risk of host 1 in the network, and the results are consistent with the actual risk of host 1, and other hosts can get the same conclusion. It can be seen that the parameters of the proposed method have excellent performance and high accuracy in network security risk quantification.