Network traffic classification method basing on CNN
Since the feature selection process will directly affect the accuracy of the traffic classification based on the traditional machine learning method,a traffic classification algorithm based on convolution neural network was tailored.First,the min-max normalization method was utilized to process the...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2018-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018018/ |
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| _version_ | 1841539446387769344 |
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| author | Yong WANG Huiyi ZHOU Hao FENG Miao YE Wenlong KE |
| author_facet | Yong WANG Huiyi ZHOU Hao FENG Miao YE Wenlong KE |
| author_sort | Yong WANG |
| collection | DOAJ |
| description | Since the feature selection process will directly affect the accuracy of the traffic classification based on the traditional machine learning method,a traffic classification algorithm based on convolution neural network was tailored.First,the min-max normalization method was utilized to process the traffic data and map them into gray images,which would be used as the input data of convolution neural network to realize the independent feature learning.Then,an improved structure of the classical convolution neural network was proposed,and the parameters of the feature map and the full connection layer were designed to select the optimal classification model to realize the traffic classification.The tailored method can improve the classification accuracy without the complex operation of the network traffic.A series of simulation test results with the public data sets and real data sets show that compared with the traditional classification methods,the tailored convolution neural network traffic classification method can improve the accuracy and reduce the time of classification. |
| format | Article |
| id | doaj-art-9bf892f418e9453b966edacb593a85c3 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2018-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-9bf892f418e9453b966edacb593a85c32025-01-14T07:14:02ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2018-01-0139142359715773Network traffic classification method basing on CNNYong WANGHuiyi ZHOUHao FENGMiao YEWenlong KESince the feature selection process will directly affect the accuracy of the traffic classification based on the traditional machine learning method,a traffic classification algorithm based on convolution neural network was tailored.First,the min-max normalization method was utilized to process the traffic data and map them into gray images,which would be used as the input data of convolution neural network to realize the independent feature learning.Then,an improved structure of the classical convolution neural network was proposed,and the parameters of the feature map and the full connection layer were designed to select the optimal classification model to realize the traffic classification.The tailored method can improve the classification accuracy without the complex operation of the network traffic.A series of simulation test results with the public data sets and real data sets show that compared with the traditional classification methods,the tailored convolution neural network traffic classification method can improve the accuracy and reduce the time of classification.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018018/network traffic classificationconvolutional neural networknormalizedfeature selection |
| spellingShingle | Yong WANG Huiyi ZHOU Hao FENG Miao YE Wenlong KE Network traffic classification method basing on CNN Tongxin xuebao network traffic classification convolutional neural network normalized feature selection |
| title | Network traffic classification method basing on CNN |
| title_full | Network traffic classification method basing on CNN |
| title_fullStr | Network traffic classification method basing on CNN |
| title_full_unstemmed | Network traffic classification method basing on CNN |
| title_short | Network traffic classification method basing on CNN |
| title_sort | network traffic classification method basing on cnn |
| topic | network traffic classification convolutional neural network normalized feature selection |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2018018/ |
| work_keys_str_mv | AT yongwang networktrafficclassificationmethodbasingoncnn AT huiyizhou networktrafficclassificationmethodbasingoncnn AT haofeng networktrafficclassificationmethodbasingoncnn AT miaoye networktrafficclassificationmethodbasingoncnn AT wenlongke networktrafficclassificationmethodbasingoncnn |