An Automatic Identification Method for Trusted Access Security Risks in Heterogeneous Fusion Communication Networks Based on Big Data
With the access of a large number of nodes,the communication network environment has become increasingly com-plex,leading to many malicious behaviors,greatly reducing the security of the communication network.In this context,in order to ensure the security of communication networks,a reliable access security risk automatic identification method based on big data for heterogeneous fusion communication networks is studied.In this study,7 access security risk factors were identified by calculating va-lidity and reliability data.Implement big data quantification processing according to quantification rules for 7 access security risk fac-tors.By constructing an identification model based on membership degree and the weight of safety risk factors,the probability value of each safety risk level occurrence is calculated.According to the principle of maximum membership degree,the risk level corre-sponding to the maximum occurrence probability is used as the identification result.The results indicate that according to the principle of maximum membership,the probability value of safety risk level occurrence corresponding to risk level L2 in condition 1 is the high-est,indicating that the identified risk level in condition 1 is low;The probability value of the safety risk level corresponding to the risk level L3 in condition 2 is the highest,indicating that the identified risk level in condition 2 is moderate;The probability value of the safety risk level corresponding to risk level L4 in condition 3 is the highest,indicating that the identified risk level in condition 3 is high.
big dataheterogeneous fusion communication networkrisk factorstrusted access security risk levelautomatic recognition method
万方数据
维普
