Fast, accurate, and lightweight real-time traffic identification method based on flow statistics

Authors:
Masaki Tai;Shingo Ata;Ikuo Oka
Affiliations:
Graduate School of Engineering, Osaka City University, Osaka, Japan;Graduate School of Engineering, Osaka City University, Osaka, Japan;Graduate School of Engineering, Osaka City University, Osaka, Japan
Venue:
PAM'07 Proceedings of the 8th international conference on Passive and active network measurement
Year:
2007

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Abstract

Recently, identification of real-time traffic online is a key technology to achieve different service to real-time and bulk applications. Previously it is easy to identify real-time by checking the protocol/port number in IP header, however, it becomes more difficult due to the existence of streaming traffic over TCP connection, overlay networks such as P2P and VPN. In this paper, we propose a new identification method for real-time traffic based on not checking the protocol number, but analyzing the statistical characteristics of packet arrivals. Our approach is fast, accurate and lightweight compared to conventional techniques.