Network Traffic Classification Method Based on Concept-adapting Very Fast Decision Tree
Yang Ji-wen · Jisuanji gongcheng · 2011
Considering Internet data stream dynamically in large volumes,this paper proposes a traffic classification method using data stream mining techniques,named Concept-adapting Very Fast Decision Tree(CVFDT).CVFDT is capable of processing dynamic datasets,coping with concept drift and updating the model catering to incoming data.The approach and naive Bayes method on network traffic data stream sets are tested, which has 12 significant attributes.Experimental result shows that the approach gets high performance on classification accuracy and spatial stability compared with naive Bayes method.