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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. ※   2012 ()  (2012R1A1A2007483)  2015   (       , K15-L01-C004-S03)  . First Author : Korea University Department of Computer and Information Science, gaek5@korea.ac.kr,  ° Corresponding Author : Korea University Department of Computer and Information Science, tmskim@korea.ac.kr,  °° Corresponding Author : University of Science & Technology, wjseok@gmail.com,  * Korea University Department of Computer and Information Science, junsang_park@korea.ac.kr,  :KICS2014-11-450, Received November 3, 2014; Revised Feburary 3, 2015; Accepted March 16, 2015 The Journal of Korean Institute of Communications and Information Sciences '15-03 Vol.40 No.03

Application Traffic Identification Speed Improvement by Optimizing Payload Signature Matching Sequence