| 基于概念漂移检测的自适应流量分类方法 |
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| 引用本文： | 姜振东,王建明,潘吴斌.基于概念漂移检测的自适应流量分类方法[J].计算机工程与应用,2019,55(3):68-75. |
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| 作者姓名： | 姜振东 王建明 潘吴斌 |
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| 作者单位： | 南京工业大学 计算机科学与技术学院,南京,211816;东南大学 计算机科学与工程学院,南京,210096 |
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| 基金项目： | 国家高技术研究发展计划（863计划） |
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| 摘 要： | 针对网络流特征会随网络环境变化而发生改变，从而导致基于流特征的机器学习分类方法精度明显降低的问题。提出一种基于概念漂移检测的自适应流量分类方法，该方法借助Kolmogorov-Smirnov检验对出现的流量进行概念漂移检测，然后通过多视图协同学习策略引入新流量样本修正概念漂移导致的模型变化，使分类器得到有效更新。实验结果表明该方法可以有效检测概念漂移并更新分类器，表现出较好的分类性能和泛化能力。
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| 关 键 词： | 概念漂移 Kolmogorov-Smirnov检验 协同学习 流量分类 |
Adaptive Traffic Classification Approach Based on Concept Drift Detection |
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| JIANG Zhendong,WANG Jianming,PAN Wubin.Adaptive Traffic Classification Approach Based on Concept Drift Detection[J].Computer Engineering and Applications,2019,55(3):68-75. |
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| Authors: | JIANG Zhendong WANG Jianming PAN Wubin |
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| Affiliation: | 1.School of Computer Science and Technology, Nanjing University of Technology, Nanjing 211816, China
2.School of Computer Science and Engineering, Southeast University, Nanjing 210096, China |
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| 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. |
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| Keywords: | concept drift Kolmogorov-Smirnov test cooperative learning traffic classification |
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