DocumentCode :
2255064
Title :
Application traffic classification using statistic signature
Author :
Hyun-Min An ; Myung-Sup Kim ; Jae-Hyun Ham
Author_Institution :
Dept. of Computer and Information Science, Korea University, Korea
fYear :
2013
fDate :
25-27 Sept. 2013
Firstpage :
1
Lastpage :
6
Abstract :
Networks today are becoming more complex and diverse because of the appearance of new applications and services. The importance, therefore, of application-level traffic classification is increasing daily. Application-level traffic classification has become a very popular area of study. Although many proposals have been presented, including port-based, payload-based and machine learning-based methods, the method that can manage all traffic has not yet been developed. More recently, methods based on statistical flow information have been studied. In this paper, we propose an application-level traffic classification methodology using the statistic signature. Our method creates a statistic signature using payload size, transmission order, and direction of the first N packets in the flow, and uses this to classify application traffic. Then, using a verification system, we prove the feasibility of our method and show its high accuracy.
Keywords :
Atmospheric measurements; Particle measurements; Reliability; Application Traffic; Statistic signature; Traffic classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network Operations and Management Symposium (APNOMS), 2013 15th Asia-Pacific
Conference_Location :
Hiroshima, Japan
Type :
conf
Filename :
6665276
Link To Document :
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