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https://bibliotecadigital.fi.uba.ar/files/original/e5412b403c67820e3804ef3a104b6ae3.pdf
a3db2296a543593d7b657f97d866277c
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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<h3>Tesis de Grado</h3>
Texto - Tesis
Metadatos procedentes de la migración desde Koha.
AIG
11630
Signatura
T 1791
Barcode
35722
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Description
An account of the resource
Grado obtenido: Ingeniero/a Electrónico de la Universidad de Buenos Aires
Disciplina: Ingeniería Electrónica
Calificación: Diez (10) Sobresaliente
Fil: Sutton, Brian. Universidad de Buenos Aires. Facultad de Ingeniería
Lista de figuras
Title
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Statistical methods for automatc Internet application recognition
Creator
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Sutton, Brian
Contributor
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Vaton, Sandrine
Dams, Alberto
Date
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2010
Subject
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METODOS ESTADISTICOS
TRAFICO DE TELECOMUNICACION
APLICACIONES DE INTERNET
INTERNET
TRANSMISION DE DATOS
Extent
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99 p.
Access Rights
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http://bibliotecadigital.fi.uba.ar/rights
Rights
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info:eu-repo/semantics/openAccess
Language
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spa
Medium
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application/pdf
Publisher
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Universidad de Buenos Aires. Facultad de Ingeniería
Abstract
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The present document introduces the research and implementation of different detection methods done on the capture platform of the Telecom Bretagne school of engineering in Brest, France. The methods developed are purely statistical based and as a premise, the payload of the packets can’t be used in order to perform the detection.
As Internet becomes a social phenomenon, more services are using the network to work. ISPs and enterprises need a tool to classify traffic and in this way decide what to do with each flow of information. It will be seen how former and quite simple detection methods became obsolete, and the new different approaches to solve this problem.
The developed methods will take different identifiers from the traffic captured and use different models to identify the kind of information flow, based on a prior learning process this platform must be put through. The learning process will result in different signatures which stand for each service.
A Theoretical introduction to every concept used to develop the methods is included, as long as two large appendixes which describe how to configure, run and modify the application implemented.
Finally, conclusions will be presented as well as the issues and considerations the ongoing research project should address in the future.
The appendixes are the guides written to help the users and developers work with the developed application.
Type
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info:eu-repo/semantics/bachelorThesis
info:ar-repo/semantics/tesis de grado
APLICACIONES DE INTERNET
INTERNET
METODOS ESTADISTICOS
TRAFICO DE TELECOMUNICACION
TRANSMISION DE DATOS