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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We analyze these patterns at three levels of increasing detail i the social, ii the functional and iii the application level.

Network packet Tracing software. We present a fundamentally different approach to classifying traffic flows according to the applications that generate them. We demonstrate the effectiveness of our approach on three real traces.

First, it operates in the darkhaving a no access to packet payload, b no knowledge of port numbers and c no additional information other than what current flow collectors provide. See our FAQ for additional information.

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Second, it can be tuned to balance the accuracy of the classification versus the number of successfully classified traffic flows.

Pavel Piskac 1 Estimated H-index: Statistical Clustering of Internet Communication Patterns. Erik Hjelmvik 2 Estimated H-index: Traffic Mining in IP Tunnels. Other Papers By First Author.

William Aiello 33 Estimated H-index: Claffy 1 Estimated H-index: This paper has 1, citations. Analysis of communities of interest in data networks.

BLINC: multilevel traffic classification in the dark – Semantic Scholar

Clqssification 3 Source Add To Collection. Download PDF Cite this paper. Rao Computer Networks Journal of Network Management Christian Dewes 2 Estimated H-index: Thomas Karagiannis 32 Estimated H-index: Moore 24 Estimated H-index: Tygar Lecture Notes in Computer Science Sung-Ho Yoon 6 Estimated H-index: Topics Discussed in This Paper.

Skip to search form Skip to main content. A parameterizable methodology for Internet traffic flow profiling. Hall University of Waikato.

BLINC: multilevel traffic classification in the dark

Gang Xiong 4 Estimated H-index: Classificatin This Paper Topics from this paper. A flow measurement architecture to preserve application structure Myungjin LeeMohammad Y. Daniele Piccitto 1 Estimated H-index: Shelton 25 Estimated H-index: These restrictions respect privacy, technological and practical constraints. In contrast to previous methods, our approach is based on observing and identifying patterns of host behavior at the transport layer.

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This paper has highly influenced other papers. Internet traffic classification using bayesian analysis techniques. This multilevel approach of looking at traffic flow is probably the most important contribution of this paper. File-sharing in the Internet: Citation Statistics 1, Citations 0 50 ’07 ’10 ’13 ‘

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