Online Internet traffic identification algorithm based on multistage classifier
Internet traffic classification plays an important role in network management. Many approaches have been proposed to classify different categories of Internet traffic. However, these approaches have specific usage contexts that restrict their ability when they are applied in the current network envi...
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| Veröffentlicht in: | China communications 2013-02, Vol.10 (2), p.89-97 |
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| container_title | China communications |
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| creator | Min, Du Xingshu, Chen Jun, Tan |
| description | Internet traffic classification plays an important role in network management. Many approaches have been proposed to classify different categories of Internet traffic. However, these approaches have specific usage contexts that restrict their ability when they are applied in the current network environment. For example, the port based approach cannot identify network applications with dynamic ports; the deep packet inspection approach is invalid for encrypted network applications; and the statistical based approach is time-consuming. In this paper, a novel technique is proposed to classify different categories of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multistage classifier. The experimental results demonstrate that this approach has high recognition rate which is up to 98% and good performance of real-time for traffic identification. |
| doi_str_mv | 10.1109/CC.2013.6472861 |
| format | Article |
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Many approaches have been proposed to classify different categories of Internet traffic. However, these approaches have specific usage contexts that restrict their ability when they are applied in the current network environment. For example, the port based approach cannot identify network applications with dynamic ports; the deep packet inspection approach is invalid for encrypted network applications; and the statistical based approach is time-consuming. In this paper, a novel technique is proposed to classify different categories of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multistage classifier. 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Many approaches have been proposed to classify different categories of Internet traffic. However, these approaches have specific usage contexts that restrict their ability when they are applied in the current network environment. For example, the port based approach cannot identify network applications with dynamic ports; the deep packet inspection approach is invalid for encrypted network applications; and the statistical based approach is time-consuming. In this paper, a novel technique is proposed to classify different categories of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multistage classifier. The experimental results demonstrate that this approach has high recognition rate which is up to 98% and good performance of real-time for traffic identification.</description><subject>Classification algorithms</subject><subject>Cryptography</subject><subject>feature selection</subject><subject>multistage classifier</subject><subject>Ports (Computers)</subject><subject>Real time systems</subject><subject>Statistical analysis</subject><subject>statistical characteristic</subject><subject>support vector machine</subject><subject>Support vector machines</subject><subject>Telecommunication traffic</subject><subject>traffic identification</subject><issn>1673-5447</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kDlvwzAMhTW0QIM0c4cuWjo60WVZGgujR4AAWbILsk25Chy5kBT0-PV1kKRcSJDfI8GH0AMlS0qJXtX1khHKl1JUTEl6g2ZUVrwohaju0CKlPZlCScklm6HtNgw-AF6HDDFAxjla53yLfQch-6my2Y8B26Efo88fB9zYBB2eWofjkH3KtgfcDjalCYZ4j26dHRIsLnmOdq8vu_q92Gzf1vXzpmiZprnQXaMYa6grm0oKKiiRnQCnOgetZIQ7rRtXAheScWW1qpxouFO2co6VuuJz9HRe-2WDs6E3-_EYw3TQ_Pb5-_Q-YYToiVuduTaOKUVw5jP6g40_hhJzcsvUtTnh5uLWpHg8KzwA_NPX6R-B7mgI</recordid><startdate>20130201</startdate><enddate>20130201</enddate><creator>Min, Du</creator><creator>Xingshu, Chen</creator><creator>Jun, Tan</creator><general>China Communications Magazine Co. 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Many approaches have been proposed to classify different categories of Internet traffic. However, these approaches have specific usage contexts that restrict their ability when they are applied in the current network environment. For example, the port based approach cannot identify network applications with dynamic ports; the deep packet inspection approach is invalid for encrypted network applications; and the statistical based approach is time-consuming. In this paper, a novel technique is proposed to classify different categories of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multistage classifier. The experimental results demonstrate that this approach has high recognition rate which is up to 98% and good performance of real-time for traffic identification.</abstract><pub>China Communications Magazine Co. Ltd</pub><doi>10.1109/CC.2013.6472861</doi><tpages>9</tpages></addata></record> |
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| ispartof | China communications, 2013-02, Vol.10 (2), p.89-97 |
| issn | 1673-5447 |
| language | eng |
| recordid | cdi_wanfang_journals_zgtx201302009 |
| source | IEEE Electronic Library (IEL) |
| subjects | Classification algorithms Cryptography feature selection multistage classifier Ports (Computers) Real time systems Statistical analysis statistical characteristic support vector machine Support vector machines Telecommunication traffic traffic identification |
| title | Online Internet traffic identification algorithm based on multistage classifier |
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