BLINC MULTILEVEL TRAFFIC CLASSIFICATION IN THE DARK PDF

This multilevel approach of looking at traffic flow is probably the most important contribution of this paper. Furthermore, our approach has two important features. BLINC. Multilevel Traffic Classification in the Dark. Thomas Karagiannis1. Konstantina Papagiannaki2. Michalis Faloutsos1. 1UC Riverside. We present a fundamentally different approach to classifying traffic flows according to the applications that generate them. In contrast to previous methods, our.

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BLINC: multilevel traffic classification in the dark – Semantic Scholar

Pieter Burghouwt 3 Estimated H-index: Toward the accurate identification of network applications Andrew W. Sung-Ho Yoon 6 Estimated H-index: File-sharing in the Internet: Thomas Karagiannis 1 Estimated H-index: Network packet Tracing software. Moore 24 Estimated H-index: Erik Hjelmvik 2 Estimated H-index: Is P2P dying or just hiding? Using of time characteristics in data flow for traffic classification. Shelton 25 Estimated H-index: Transport layer Traffic flow Computer network Computer security Computer science Distributed computing Payload Port computer networking Network packet Traffic classification.

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Internet application traffic classification using fixed IP-port.

Are you looking for Furthermore, our approach has two important features. Gang Xiong 4 Estimated H-index: Cited 3 Source Add To Collection.

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Skip to search form Skip to main content. In contrast to previous methods, our approach is based on observing and classificaton patterns of host behavior at the transport layer. Citation Statistics 1, Citations 0 50 ’07 ’10 ’13 ‘ Other Papers By First Author. We analyze these patterns at three levels of increasing detail i the social, ii the functional and iii the application level. KleinbergDoug J.

By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy PolicyTerms of Serviceand Dataset License. Hall University of Waikato. Daniele Piccitto 1 Estimated H-index: First, it operates in the darkhaving a no access to packet payload, clsssification no knowledge of port numbers and c no additional information other than what current flow collectors provide.

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We analyze these patterns at three levels of increasing detail i the social, ii the functional and iii the application level. Topics Discussed in This Paper. Andrea Baiocchi 17 Estimated H-index: Thomas Karagiannis 32 Estimated H-index: Supporting the visualization and forensic analysis of network events.

These restrictions respect privacy, technological and practical constraints. This multilevel approach of looking at traffic flow is probably the most important contribution of this paper. This paper has highly influenced other papers.

Terry Winograd 61 Estimated H-index: Internet traffic classification using bayesian analysis techniques. Analysis of communities of interest in data networks.