Cloud-model based decision-making for network risk assessment

Abstract

In order to assess the risk of network security more reasonably,a cloud-model based method for network risk assessment was proposed.It took advantage of cloud model featuring perfect combination of randomness and fuzziness.Firstly,standard clouds were constructed by sampling normal system status.When making risk assessments,the current risk state was sampled to calculate the cloud characteristics,then the cloud similarity algorithm based on the distance measurement of cloud droplets was used to calculate the similarity between them,and the biggest similarity was the final output.Finally,Kddcup99 data set was used to do simulated attack and performance sampling test.The experimental results show that the proposed method retains the maximum uncertainty of network intrusion assessment and improves the credibility of the results.