Performance Improvement of Traffic Identification by Categorizing Signature Matching Type 


Vol. 40,  No. 7, pp. 1339-1346, Jul.  2015


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  Abstract

The traffic identification is a preliminary and essential step for stable network service provision and efficient network resource management. While a number of identification methods have been introduced in literature, the payload signature-based identification method shows the highest performance in terms of accuracy, completeness, and practicality. However, the payload signature-based method"s processing speed is much slower than other identification method such as header-based and statistical methods. In this paper, we first classifies signatures by matching type based on range, order, and direction of packet in a flow which was automatically extracted. By using this classification, we suggest a novel method to improve processing speed of payload signature-based identification by reducing searching space.

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  Cite this article

[IEEE Style]

W. Jung, J. Park, M. Kim, "Performance Improvement of Traffic Identification by Categorizing Signature Matching Type," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 7, pp. 1339-1346, 2015. DOI: .

[ACM Style]

Woo-Suk Jung, Jun-Sang Park, and Myung-Sup Kim. 2015. Performance Improvement of Traffic Identification by Categorizing Signature Matching Type. The Journal of Korean Institute of Communications and Information Sciences, 40, 7, (2015), 1339-1346. DOI: .

[KICS Style]

Woo-Suk Jung, Jun-Sang Park, Myung-Sup Kim, "Performance Improvement of Traffic Identification by Categorizing Signature Matching Type," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 7, pp. 1339-1346, 7. 2015.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880