Analyzing peer-to-peer traffic across large networks
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Accurate, scalable in-network identification of p2p traffic using application signatures
Proceedings of the 13th international conference on World Wide Web
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Automated Traffic Classification and Application Identification using Machine Learning
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Identifying Known and Unknown Peer-to-Peer Traffic
NCA '06 Proceedings of the Fifth IEEE International Symposium on Network Computing and Applications
On the validation of traffic classification algorithms
PAM'08 Proceedings of the 9th international conference on Passive and active network measurement
Software architecture for a lightweight payload signature-based traffic classification system
TMA'11 Proceedings of the Third international conference on Traffic monitoring and analysis
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As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic classification becomes important for the effective use of network resources. In this paper, we present an application traffic classification method based on fixed IP-port information. A fixed IP-port is a {IP, protocol, port} triple dedicated to only one application, which is automatically collected from the behavior analysis of individual applications. We can classify the Internet traffic accurately and quickly by simple packet header matching to the collected fixed IP-port information. Therefore, we can construct a lightweight, fast, and accurate real-time traffic classification system than other classification method. In this paper we propose a novel algorithm to extract the fixed IP-port information and the system architecture. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.