Communication Network Security Situation Prediction Technology based on Big Data Clustering
Traditional communication network security situation prediction technology lacks the sup-port of big data,and it was difficult to classify and track the attacks in detail,which leads to slow convergence and low accuracy in long-term situation prediction.A communication network security situation prediction technology based on big data clustering was proposed.The attributes and charac-teristics of communication network are analyzed,the first level of security situation description index was selected,and the second level index was subdivided after standardized data processing.The big data clustering algorithm was optimized,the optimal clustering number was calculated,the clustering center was determined,the association rule library was established and the prediction process was op-timized,and the design of communication network security situation prediction technology based on big data clustering was completed.Experimental results show that compared with the two traditional security situation prediction techniques,the designed technique has a faster convergence rate,and all data points do not appear residual diffusion phenomenon,and the data integrity was high.
big data clusteringcommunication networksecurity situationdescription indexclus-tering optimizationconvergence rate
万方数据
维普
