지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.1
- 수록면
- 404 - 407 (4page)
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초록· 키워드
오류제보하기
As network traffic is dramatically increasing, classification of application traffic becomes important for the effective use of network resources. Classification of network traffic using port-based or payload-based analysis is becoming increasingly difficult because of many peer-to-peer (P2P) applications using dynamic port numbers, masquerading techniques, and encryption. An alternative approach is to classify traffic by exploiting the distinctive characteristics of applications. In this letter, we propose a classification method of application traffic using statistic signatures based on SVM (Support Vector Machine). The statistic signatures, defined as a directional sequence of packet size in a flow, are collected for each application, and applications are classified by SVM mechanism.
목차
SUMMARY
Ⅰ. Introduction
Ⅱ. Related Works
Ⅲ. Our Classification Method
Ⅳ. Simulations
Ⅴ. Simulations
References
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UCI(KEPA) : I410-ECN-0101-2014-560-003064857