Research of P2P traffic identification based on naive Bayes and decision tables combination algorithm

Author

Xu, He ; Wang, Suoping ; Wang, Ruchuan ; Zhao, Dan

Author_Institution

Inst. of Inf. Network Technol., Nanjing, China

Volume

6

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

2875

Lastpage

2879

Abstract

A novel P2P traffic identification method based on the combination of naive Bayes and decision tables is proposed, which uses Fast Correlation-Based Filter (FCBF) algorithm to extract P2P flow characteristics, and utilises six DTNB (combination of naive Bayes and decision tables) combined with dynamic weighted integration method to set up a P2P flow detection model. Through experimental comparison between this proposed model and traditional methods, such as single DTNB, decision tree and naive Bayes, we find that the proposed method has a better P2P traffic identification accuracy and stability.

Keywords

Bayes methods; decision tables; filtering theory; peer-to-peer computing; telecommunication traffic; trees (mathematics); FCBF algorithm; P2P flow detection model; P2P traffic identification; decision tables combination algorithm; decision tree; fast correlation-based filter; naive Bayes; Accuracy; Classification algorithms; IP networks; Internet; Machine learning; Niobium; Software; P2P; decision tree; naive Bayes; traffic identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5931-5

Type

conf

DOI

10.1109/FSKD.2010.5569265

Filename

5569265