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.

Author: Arakasa Moogurr
Country: Belarus
Language: English (Spanish)
Genre: Life
Published (Last): 14 May 2008
Pages: 285
PDF File Size: 20.93 Mb
ePub File Size: 16.94 Mb
ISBN: 211-6-33871-832-3
Downloads: 65517
Price: Free* [*Free Regsitration Required]
Uploader: Garg

BLINC: multilevel traffic classification in the dark – Semantic Scholar

Is P2P dying or just hiding? An analysis of Internet chat systems. Using of time characteristics in data flow for traffic classification.

See our FAQ for additional information. Claffy 1 Estimated H-index: Sung-Ho Yoon 6 Estimated H-index: Alberto Dainotti 20 Estimated H-index: Erik Hjelmvik 2 Estimated H-index: Analysis of communities of interest in data networks.

Moore 24 Estimated Clasification Supporting the visualization and forensic analysis of network events. Topics Discussed in This Paper. KleinbergDoug J.

  DANLOD ROMAN ASHEGHANE PDF

Thomas Karagiannis 32 Estimated H-index: Internet traffic classification using bayesian analysis techniques. Hall University of Waikato. Semantic Scholar estimates that this publication has 1, citations based on the available data.

Terry Winograd 61 Estimated H-index: This multilevel approach of looking at traffic flow is probably the most important contribution of this paper. We present a fundamentally different approach to classifying traffic flows according to the applications that generate them. Tygar Lecture Notes in Computer Mhltilevel Skip to search form Skip mulyilevel main content. Pavel Piskac 1 Estimated H-index: 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.

Toward the accurate identification of network applications. Architecture of a network monitor. These restrictions respect privacy, technological and practical constraints.

We demonstrate the effectiveness of our approach on three real traces. Daniele Piccitto 1 Estimated H-index: Thomas Karagiannis 1 Estimated H-index: Gang Xiong 4 Estimated H-index: File-sharing in the Internet: Toward the accurate identification of network applications Andrew W.

  BRAD MEHLDAU ELEGIAC CYCLE TRANSCRIPTION PDF

Second, it can be tuned to balance the accuracy of the classification versus the number of successfully classified traffic flows. Multiilevel paper has highly influenced other papers.

BLINC: multilevel traffic classification in the dark

Citations Publications citing this paper. Cited 3 Source Add To Collection. Traffic Mining in IP Tunnels. Statistical Clustering of Internet Communication Patterns. Rao Computer Networks This paper has 1, citations. From This Paper Topics from this paper.

William Aiello 33 Estimated H-index: Pieter Burghouwt 3 Estimated H-index: We analyze these patterns at three levels of increasing detail i the social, ii the functional and iii the application level. Citation Statistics 1, Citations 0 50 ’07 ’10 ’13 ‘

Posted in Art