Fast application-level traffic classification using NetFlow records
In order to improve the performance and reduce the resources usage of application-level traffic classification,a novel fast application-level traffic classification(FATC) algorithm using IP flow record from NetFlow as input was presented.FATC adopted metric selection algorithm based on correlation c...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2012-01-01
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| Series: | Tongxin xuebao |
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| Online Access: | http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)01-0145-08/ |
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| _version_ | 1841539936722878464 |
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| author | Liang CHEN Jian GONG |
| author_facet | Liang CHEN Jian GONG |
| author_sort | Liang CHEN |
| collection | DOAJ |
| description | In order to improve the performance and reduce the resources usage of application-level traffic classification,a novel fast application-level traffic classification(FATC) algorithm using IP flow record from NetFlow as input was presented.FATC adopted metric selection algorithm based on correlation coefficient to measure the correlation among flow metric variables,and deleted the irrelevant or redundant metrics,then used Bayes discrimination to classify network traffic to the application category that of smallest misjudge loss.The theoretical analysis and experimental results show that,with more than 95% accuracy,the FATC algorithm greatl reduces the time and space complexity of current application-level traffic classification algorithms during the training and classification processes,and can work efficiently on 10Gbit/s backbone network in real time. |
| format | Article |
| id | doaj-art-346ef9ef8e7a4a16bf16a2e5ffae2c63 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2012-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-346ef9ef8e7a4a16bf16a2e5ffae2c632025-01-14T06:31:00ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2012-01-013314515259659736Fast application-level traffic classification using NetFlow recordsLiang CHENJian GONGIn order to improve the performance and reduce the resources usage of application-level traffic classification,a novel fast application-level traffic classification(FATC) algorithm using IP flow record from NetFlow as input was presented.FATC adopted metric selection algorithm based on correlation coefficient to measure the correlation among flow metric variables,and deleted the irrelevant or redundant metrics,then used Bayes discrimination to classify network traffic to the application category that of smallest misjudge loss.The theoretical analysis and experimental results show that,with more than 95% accuracy,the FATC algorithm greatl reduces the time and space complexity of current application-level traffic classification algorithms during the training and classification processes,and can work efficiently on 10Gbit/s backbone network in real time.http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)01-0145-08/computer system architecturetraffic classificationNetFlowcorrelation coefficientfeature selectionBayes discrimination |
| spellingShingle | Liang CHEN Jian GONG Fast application-level traffic classification using NetFlow records Tongxin xuebao computer system architecture traffic classification NetFlow correlation coefficient feature selection Bayes discrimination |
| title | Fast application-level traffic classification using NetFlow records |
| title_full | Fast application-level traffic classification using NetFlow records |
| title_fullStr | Fast application-level traffic classification using NetFlow records |
| title_full_unstemmed | Fast application-level traffic classification using NetFlow records |
| title_short | Fast application-level traffic classification using NetFlow records |
| title_sort | fast application level traffic classification using netflow records |
| topic | computer system architecture traffic classification NetFlow correlation coefficient feature selection Bayes discrimination |
| url | http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)01-0145-08/ |
| work_keys_str_mv | AT liangchen fastapplicationleveltrafficclassificationusingnetflowrecords AT jiangong fastapplicationleveltrafficclassificationusingnetflowrecords |