基于贝叶斯方法的网络安全态势感知模型

为全面、准确地分析既定网络的安全态势并给出态势等级评定,提出一种基于贝叶斯方法的网络安全态势感知混合模型。对既定网络环境中收集到的态势指标数据进行离散化预处理,利用不同的评价方法建立相应的态势指标分级模型,并将分级模型底层的态势影响指标通过贝叶斯网络模型逐层向上融合至态势层,得到最终评价指标进行网络态势评定。实验结果表明,该模型满足实际应用要求,评估结果准确、有效,能够提高网络环境的稳定性和可靠性。

Network Security Situation Awareness Model Based on Bayesian Method

To comprehensively and accurately analyze the security situation of a given network and evaluate the situation,this paper proposes a mixed Network Security Situation Awareness(NASS)model based on Bayesian method.The model preprocesses the situation indicator data collected from a given network environment by discretizing them.Then according to the different evaluation methods,the hierarchical model of situation indicators is established.Finally,the situation influence indicators at the bottom layer of the hierarchical model are merged upward layer by layer by using the Bayesian network model,and the final evaluation index of network security situation is obtained to give the status rating.Experimental results show that the proposed model meets the practical requirements of applications,and the evaluation results are accurate and effective,improving the stability and reliability of network environment.