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http://dx.doi.org/10.9708/jksci.2014.19.3.045

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

Ye, Wujian (Dept. of Computer, Dankook University)
Cho, Kyungsan (Dept. of Software Science, Dankook University)
Publication Information
Journal of the Korea Society of Computer and Information / v.19, no.3, 2014 , pp. 45-54 More about this Journal
Abstract
In this paper, an improved two-step P2P traffic classification scheme is proposed to overcome the limitations of the existing methods. The first step is a signature-based classifier at the packet-level. The second step consists of pattern heuristic rules and a statistics-based classifier at the flow-level. With pattern heuristic rules, the accuracy can be improved and the amount of traffic to be classified by statistics-based classifier can be reduced. Based on the analysis of different decision tree algorithms, the statistics-based classifier is implemented with REPTree. In addition, 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 higher accuracy and lower overhead compared to other existing schemes.
Keywords
P2P traffic classification; hybrid scheme; signature-based; heuristic rules; decision tree;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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