Study on Process of Network Traffic Classification Using Machine Learning

Jianmin Wang, Cheng-Lu Qian, Chunhui Che, Haitao He
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引用次数: 7

Abstract

Classification of network traffic is the essential step for many network researches. Machine learning based approach is one of the most important approaches in the field of network traffic classification. Many related algorithms have been issued by researchers while the whole process contains a series of steps except building the algorithm and few researchers perform description. In this paper, a detailed workflow of machine learning based network traffic classification in campus network of SunYat-sen University is described, including steps such as data preparation and model construction. In the latter part of the paper, simple experiments are performed to prove the effectiveness of machine learning approach.
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基于机器学习的网络流量分类过程研究
网络流量分类是许多网络研究的关键步骤。基于机器学习的方法是网络流量分类领域中最重要的方法之一。研究人员提出了许多相关的算法,但整个过程除了构建算法之外还包含一系列步骤,很少有研究人员进行描述。本文详细介绍了基于机器学习的中山大学校园网网络流量分类的工作流程,包括数据准备和模型构建等步骤。在本文的后半部分,通过简单的实验来证明机器学习方法的有效性。
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