关键词: 概念漂移, Kolmogorov-Smirnov检验, 协同学习, 流量分类

Abstract: For network traffic characteristics will change with the change of network environment, which causes a significant reduction on the accuracy of traffic classification method based on machine learning. This paper proposes an adaptive traffic classification method based on concept drift detection, the method adopts Kolmogorov-Smirnov test to detect traffic concept drift, and then the classifier to be effectively updated through multi-view cooperative schema by introduction of new coming traffic in response to revise the model change caused by concept drift. Experimental results show that the method can effectively detect concept drift and update the classifier it has high accuracy and generalization.

Key words: concept drift, Kolmogorov-Smirnov test, cooperative learning, traffic classification