基于组合模型的网络安全态势估计

Network Security Situation Assessment Based on Combination Model

为了获得更加理想的网络安全态势估计效果,提出一种基于组合方法的网络安全态势估计模型。首先收集网络安全态势样本,进行预处理得到学习样本,然后将训练样本集输入到BP神经网络进行学习,并采用布谷鸟搜索算法选择最合理的BP神经网络参数,最后通过仿真实验对模型性能进行分析。结果表明,本文模型大幅度降低了网络安全态势的拟合误差和预测误差,是一种科学、合理的网络安全态势估计模型,估计结果具有一定的实际应用价值。

In order to obtain more ideal estimate effect of network security situation, this paper proposed an estimation model based on network security situational combination method. Firstly, samples of network security situation were collected and processed to get the learning samples. Secondly, the training sample sets were input to the BP neural network to learn, and the cuckoo search algorithm was adopted to select the most reasonable parameters of the BP neural network. Finally the simulation experiments were used to analyze the performance of model. The results show that, the proposed model greatly reduces the fitting error and the prediction error of network security situation, it is a scientific, reasonable estimation model of network security situation, and the estimation results have a certain practical application value.