P2P Traffic Classification using Advanced Heuristic Rules and Analysis of Decision Tree Algorithms (개선된 휴리스틱 규칙 및 의사 결정 트리 분석을 이용한 P2P 트래픽 분류 기법)

예우지엔; Kyungsan CHO (조경산)

P2P Traffic Classification using Advanced Heuristic Rules and Analysis of Decision Tree Algorithms

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2014, 19(3), pp.45~54
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

예우지엔 ¹, Kyungsan CHO ¹

¹단국대학교

Accredited

ABSTRACT

In this paper, an improved two-step P2P traffic classification scheme is proposed to overcomethe limitations of the existing methods. The first step is a signature-based classifier at thepacket-level. The second step consists of pattern heuristic rules and a statistics-based classifier atthe flow-level. With pattern heuristic rules, the accuracy can be improved and the amount oftraffic to be classified by statistics-based classifier can be reduced. Based on the analysis ofdifferent decision tree algorithms, the statistics-based classifier is implemented with REPTree. Inaddition, the ensemble algorithm is used to improve the performance of statistics-based classifier. Through the verification with the real datasets, it is shown that our hybrid scheme provides higheraccuracy and lower overhead compared to other existing schemes.

KEYWORDS

P2P traffic classification, hybrid scheme, signature-based, heuristic rules, decision tree

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