Improving network intrusion detection with extended KDD features

Edward Paul Guillén, Jhordany Rodríguez Parra, Rafael Vicente Paéz Mendez

Producción: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

In order to analyze results of anomaly detection methods for Network Intrusion Detection Systems, the DARPA KDD data set have been widely analyzed but their data are outdated for most kinds of attacks. A software called Spleen designed to get data from a tested network with the same structure of DARPA data set is introduced. The application is used to complete the data set with additional features according to an attack analysis. Finally, to show advantages of an extended data set, two genetic methods in the detection of non-content based attacks are tested.

Idioma originalInglés
Título de la publicación alojadaIAENG Transactions on Engineering Technologies - Special Issue of the World Congress on Engineering and Computer Science 2012
EditorialSpringer Verlag
Páginas431-445
Número de páginas15
ISBN (versión impresa)9789400768178
DOI
EstadoPublicada - 2014
EventoWorld Congress on Engineering and Computer Science, WCECS 2012 - San Francisco, CA, Estados Unidos
Duración: 24 oct. 201226 oct. 2012

Serie de la publicación

NombreLecture Notes in Electrical Engineering
Volumen247 LNEE
ISSN (versión impresa)1876-1100
ISSN (versión digital)1876-1119

Conferencia

ConferenciaWorld Congress on Engineering and Computer Science, WCECS 2012
País/TerritorioEstados Unidos
CiudadSan Francisco, CA
Período24/10/1226/10/12

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