Solving the app-level classification problem of P2P traffic Via optimized support vector machines

Rui Wang; Yang Liu; Yuexiang Yang; Xiaoyong Zhou

doi:10.1109/ISDA.2006.253893

Solving the app-level classification problem of P2P traffic Via optimized support vector machines

Rui Wang^*
, Yang Liu
, Yuexiang Yang
, Xiaoyong Zhou

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

33 Citations (Scopus)

Abstract

Since the emergence of peer-to-peer (P2P) networking in the last 90s, P2P traffic has become one of the most significant portion of the network traffic. Accurate identification of P2P traffic makes great sense for efficient network management and reasonable utility of network resources. App-level classification of P2P traffic, especially without payload feature detection, is still a challenging problem. This paper proposes a new method for P2P traffic identification and app-level classification, which merely uses transport layer information. The method uses optimized Support Vector Machines to perform large learning tasks, which is common in network traffic identification. The experimental results show that the proposed method has high efficiency and promising accuracy.

Original language	English
Title of host publication	Proceedings - ISDA 2006
Subtitle of host publication	Sixth International Conference on Intelligent Systems Design and Applications
Editors	Yuehui Chen, Ajith Abraham
Pages	534-539
Number of pages	6
DOIs	https://doi.org/10.1109/ISDA.2006.253893
Publication status	Published - 16 Oct 2006
Event	ISDA: 2006 Sixth International Conference on Intelligent Systems Design and Applications - Jinan, China Duration: 16 Oct 2006 → 18 Oct 2006

Publication series

Name	Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications

Conference

Conference	ISDA: 2006 Sixth International Conference on Intelligent Systems Design and Applications
Country/Territory	China
City	Jinan
Period	16/10/06 → 18/10/06

Access to Document

10.1109/ISDA.2006.253893

Cite this

Wang, R., Liu, Y., Yang, Y., & Zhou, X. (2006). Solving the app-level classification problem of P2P traffic Via optimized support vector machines. In Y. Chen, & A. Abraham (Eds.), Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications (pp. 534-539). (Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications). https://doi.org/10.1109/ISDA.2006.253893

Wang, Rui ; Liu, Yang ; Yang, Yuexiang et al. / Solving the app-level classification problem of P2P traffic Via optimized support vector machines. Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications. editor / Yuehui Chen ; Ajith Abraham. 2006. pp. 534-539 (Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications).

@inproceedings{78d92be006e14c5ca22e012be6df1ecf,

title = "Solving the app-level classification problem of P2P traffic Via optimized support vector machines",

abstract = "Since the emergence of peer-to-peer (P2P) networking in the last 90s, P2P traffic has become one of the most significant portion of the network traffic. Accurate identification of P2P traffic makes great sense for efficient network management and reasonable utility of network resources. App-level classification of P2P traffic, especially without payload feature detection, is still a challenging problem. This paper proposes a new method for P2P traffic identification and app-level classification, which merely uses transport layer information. The method uses optimized Support Vector Machines to perform large learning tasks, which is common in network traffic identification. The experimental results show that the proposed method has high efficiency and promising accuracy.",

author = "Rui Wang and Yang Liu and Yuexiang Yang and Xiaoyong Zhou",

note = "Publisher Copyright: {\textcopyright} 2006, IEEE; ISDA: 2006 Sixth International Conference on Intelligent Systems Design and Applications ; Conference date: 16-10-2006 Through 18-10-2006",

year = "2006",

month = oct,

day = "16",

doi = "10.1109/ISDA.2006.253893",

language = "English",

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series = "Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications",

pages = "534--539",

editor = "Chen, \{Yuehui \} and Abraham, \{Ajith \}",

booktitle = "Proceedings - ISDA 2006",

}

Wang, R, Liu, Y, Yang, Y & Zhou, X 2006, Solving the app-level classification problem of P2P traffic Via optimized support vector machines. in Y Chen & A Abraham (eds), Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications. Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications, pp. 534-539, ISDA: 2006 Sixth International Conference on Intelligent Systems Design and Applications, Jinan, China, 16/10/06. https://doi.org/10.1109/ISDA.2006.253893

Solving the app-level classification problem of P2P traffic Via optimized support vector machines. / Wang, Rui; Liu, Yang; Yang, Yuexiang et al.
Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications. ed. / Yuehui Chen; Ajith Abraham. 2006. p. 534-539 (Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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T1 - Solving the app-level classification problem of P2P traffic Via optimized support vector machines

AU - Wang, Rui

AU - Liu, Yang

AU - Yang, Yuexiang

AU - Zhou, Xiaoyong

PY - 2006/10/16

Y1 - 2006/10/16

N2 - Since the emergence of peer-to-peer (P2P) networking in the last 90s, P2P traffic has become one of the most significant portion of the network traffic. Accurate identification of P2P traffic makes great sense for efficient network management and reasonable utility of network resources. App-level classification of P2P traffic, especially without payload feature detection, is still a challenging problem. This paper proposes a new method for P2P traffic identification and app-level classification, which merely uses transport layer information. The method uses optimized Support Vector Machines to perform large learning tasks, which is common in network traffic identification. The experimental results show that the proposed method has high efficiency and promising accuracy.

AB - Since the emergence of peer-to-peer (P2P) networking in the last 90s, P2P traffic has become one of the most significant portion of the network traffic. Accurate identification of P2P traffic makes great sense for efficient network management and reasonable utility of network resources. App-level classification of P2P traffic, especially without payload feature detection, is still a challenging problem. This paper proposes a new method for P2P traffic identification and app-level classification, which merely uses transport layer information. The method uses optimized Support Vector Machines to perform large learning tasks, which is common in network traffic identification. The experimental results show that the proposed method has high efficiency and promising accuracy.

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DO - 10.1109/ISDA.2006.253893

M3 - Conference proceeding

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T3 - Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications

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Wang R, Liu Y, Yang Y, Zhou X. Solving the app-level classification problem of P2P traffic Via optimized support vector machines. In Chen Y, Abraham A, editors, Proceedings - ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications. 2006. p. 534-539. (Proceedings - ISDA: International Conference on Intelligent Systems Design and Applications). doi: 10.1109/ISDA.2006.253893

Solving the app-level classification problem of P2P traffic Via optimized support vector machines

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