A New Method of Network Risk Assessment Based on Bayesian Model
Abstract
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.
DOI
10.12783/dtcse/ccnt2020/35444
10.12783/dtcse/ccnt2020/35444
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