Real time automation prediction system for 5G communication network security based on multi-source data-driven
A single data source may not be able to provide comprehensive information,leading to bias in 5G communication net-work security prediction results.To solve the above problems,an automated real-time prediction system for 5G communication net-work security driven by multi-source data is designed.Design system framework based on Model-View-Controller architecture,de-sign system database for storing multi-source data;The probe collector and Flume collector are used to collect multi-source data,and the data is transferred to the database through the middleware.The dimensionality of multi-source data is reduced by gray relational degree method to extract key data.The security of 5G communication network is quantified and taken as the dependent variable,and the key multi-source data is taken as the independent variable,and the multiple regression prediction model is constructed to realize the automatic real-time prediction of 5G communication network security.The test results show that the determination coefficient of the regression prediction model is above 0.9,which proves that the prediction accuracy of the designed system is higher.
multi-source data-driven5G communication networknetwork securityprediction system
万方数据
维普
