Application Traffic Identification Speed Improvement by Optimizing Payload Signature Matching Sequence 


Vol. 40,  No. 3, pp. 575-585, Mar.  2015


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  Abstract

The traffic classification is a preliminary and essential step for stable network service provision and efficient network resource management. However, the payload signature-based method has significant drawbacks in high-speed network environment that the processing speed is much slower than other methods such as header-based and statistical methods. In addition, as signature numbers are increasing, traffic analysis speed also declines because of signature matching method that does not consider analytic efficiency of each signature and traffic occurrence feature. In this paper, we propose a signature list reordering method in order by analytic value of each signature. When we reordered the signature list by the proposed method, we achieved about 30% improvement in speed of the traffic analysis compared with random signature list.

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  Cite this article

[IEEE Style]

S. Lee, J. Park, M. Kim, W. Seok, "Application Traffic Identification Speed Improvement by Optimizing Payload Signature Matching Sequence," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 3, pp. 575-585, 2015. DOI: .

[ACM Style]

Sung-ho Lee, Jun-sang Park, Myung-sup Kim, and Woojin Seok. 2015. Application Traffic Identification Speed Improvement by Optimizing Payload Signature Matching Sequence. The Journal of Korean Institute of Communications and Information Sciences, 40, 3, (2015), 575-585. DOI: .

[KICS Style]

Sung-ho Lee, Jun-sang Park, Myung-sup Kim, Woojin Seok, "Application Traffic Identification Speed Improvement by Optimizing Payload Signature Matching Sequence," The Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 3, pp. 575-585, 3. 2015.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880