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.
|Published (Last):||22 January 2011|
|PDF File Size:||10.68 Mb|
|ePub File Size:||18.54 Mb|
|Price:||Free* [*Free Regsitration Required]|
Furthermore, our approach has two important features. Thomas Karagiannis 1 Estimated H-index: Claffy 1 Estimated H-index: A flow measurement architecture to preserve application structure Myungjin LeeMohammad Y.
BLINC: multilevel traffic classification in the dark – Semantic Scholar
Supporting the visualization and forensic analysis of boinc events. We analyze these patterns at three levels of increasing detail i the social, ii the functional and iii the application level. Gang Xiong 4 Estimated H-index: Shelton 25 Estimated H-index: Pieter Burghouwt 3 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 myltilevel provide.
Citation Statistics 1, Citations 0 50 ’07 ’10 ’13 ‘ From This Paper Topics from this paper. Using of time characteristics in data flow for traffic classification.
Skip to search form Skip to main content. File-sharing in the Internet: William Aiello 33 Estimated H-index: Is P2P dying or just hiding?
BLINC: multilevel traffic classification in the dark
Architecture of a network monitor. Transport layer Traffic classificatino Computer network Computer security Computer science Distributed computing Payload Port computer networking Network packet Traffic classification. Pavel Piskac 1 Estimated H-index: KleinbergDoug J.
A continuous time bayesian network approach for intrusion detection. In contrast to previous methods, our approach is based on observing and identifying patterns of host behavior at the transport layer.
Journal of Network Management Terry Winograd 61 Estimated H-index: Rao Computer Networks A parameterizable methodology for Internet traffic flow profiling. In contrast to previous methods, our approach is based on observing and identifying patterns of host behavior at the transport layer.
An analysis of Internet chat systems. Toward the accurate identification of network applications. We present a fundamentally flassification approach to classifying traffic flows according to the applications that generate them.
See our FAQ for additional information. Cited 3 Source Add To Collection. Hall University of Waikato. Topics Discussed in This Paper.
Moore 24 Estimated H-index: Daniele Piccitto 1 Estimated H-index: This multilevel approach of looking at traffic flow is probably the most important contribution of this paper.
Network packet Tracing software. Sung-Ho Yoon 6 Estimated H-index: Erik Hjelmvik 2 Estimated H-index: Alberto Dainotti 20 Estimated H-index: