Internet traffic classification using bayesian analysis techniques
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Toward the accurate identification of network applications
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
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When we reverse-engineer unknown protocols or analyze the Internet traffic, it is critical to capture complete traffic traces generated by a target application. Besides, to prove the accuracy of Internet traffic classification algorithms of the traffic monitoring system usually located in the middle of the network, it is highly required to retain traffic traces associated with the related application. Therefore, in this paper, we present an application-specific packet capturing method at end hosts, which is based on the dynamic kernel probing technique. From the experiments it is shown that the proposed method is useful for creating per-application complete traffic traces without performance degradation.