基于贝叶斯模型的网络风险评估新方法

Kunfu Wang, Wei Feng, Xing Li
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引用次数: 0

摘要

为了帮助网络管理员对网络安全风险进行评估,提出了一种新的网络风险评估方法贝叶斯模型。首先,该模型设计了攻击收益和攻击成本指标的定量方法,引入原子攻击效率变量,并将该变量整合到概率的计算中,得到网络中各节点的先验风险概率,从而对网络风险进行静态评估。其次,提出删除节点顺序的DNO_Alg来确定消除元素的顺序,从而将贝叶斯模型转化为聚类树;最后,结合检测到的攻击,采用聚类树传播算法动态计算节点的后验风险概率,实时评估网络风险。
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A New Method of Network Risk Assessment Based on Bayesian Model
In order to assist network administrators to assess network security risks, a new Bayesian model of network risk assessment method is proposed. Firstly, the model designs the quantitative method of attack revenue and attack cost index, introduces the atomic attack efficiency variable, and integrates the variable into the calculation of probability, obtains the prior risk probability of each node in the network, so as to carry out the static evaluation of network risk. Secondly, DNO_Alg of deleting node order is proposed to determine the order of eliminating elements, so that Bayesian model can be transformed into cluster tree. Finally, combined with the detected attacks, the cluster tree propagation algorithm is used to dynamically calculate the posterior risk probability of nodes, so as to evaluate the network risk in real time.
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