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dc.date.accessioned 2012-11-08T11:53:11Z
dc.date.available 2012-11-08T11:53:11Z
dc.date.issued 2012-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23846
dc.description.abstract The fast evolution of Botnet malware made it extremely difficult to detect. Despite it can be just considered as a tool, nowadays it has become one of the most dangerous threats for system administrators. Botnets are used as the starting point for di erent kind of attacks, such as SPAM, Denegation of Service, key logging and tra c sni ng, among others. In this paper we analyze some of the most relevant network tra c characteristics used for Botnet recognition. We have reviewed the most important works in the eld of Botnet detection and have carried out an analysis in order to establish which are more appropriate to describe the Botnet behavior. Our final goal is to provide to network administrators the bases for building tools that can help them in their daily ght against this security threat. en
dc.language en es
dc.subject network traffic es
dc.subject informática es
dc.subject Botnet detection es
dc.title An analysis of network traffic characteristics for Botnet detection en
dc.type Objeto de conferencia es
sedici.creator.person Erquiaga, María José es
sedici.creator.person Catania, Carlos es
sedici.creator.person García Garino, Carlos es
sedici.description.note Eje: Workshop de seguridad informática (WSI) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2012-10
sedici.relation.event XVIII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)