The large amount of network traffic generated by Internet applications brings great challenges to Internet security. In order to facilitate network management and realize automatic classification of network traffic, this paper proposes a network traffic classification model NTCNET based on CNNs. Use open data set to do simulation verification experiment, then compare the test results with a variety of traditional classification methods. The experimental results shows that the constructed traffic classification model NTCNET has better precision, robustness and accuracy, with an accuracy of 99.66%.

中文翻译：

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使用深度学习的网络流量分类

互联网应用程序产生的大量网络流量给互联网安全带来了巨大挑战。为了便于网络管理，实现网络流量的自动分类，本文提出了一种基于CNNs的网络流量分类模型NTCNET。使用开放数据集进行模拟验证实验，然后将测试结果与多种传统分类方法进行对比。实验结果表明，构建的流量分类模型NTCNET具有较好的精度、鲁棒性和准确率，准确率达到99.66%。