Internet Traffic Classification Based on Decision Tree
Traffic classification or application identification is an essential step for a number of network issues including management,security and research.The diminished effectiveness of traditional port-based traffic classifier and the overheads of deep packet inspection approaches motivate new techniques.It has been proved that traffic statistics can discriminate between applications,in this paper,we propose a supervised method based on boosted C4.5 decision tree classifier.Experiment results show that C4.5 classifier can perform fast classification and achieve high accuracy;while boosted C4.5 classifier achieves higher accuracy with much longer training time and slightly slower classify rate.