Visualization and clustering for SNMP intrusion detection

Accurate intrusion detection is still an open challenge. The present work aims at being one step toward that purpose by studying the combination of clustering and visualization techniques. To do that, the mobile visualization connectionist agent-based intrusion detection system (MOVICAB-IDS), previo...

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Detalles Bibliográficos
Autores: Sánchez, Raúl, Herrero Cosío, Álvaro, Corchado, Emilio
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2013
País:España
Institución:Universidad de Burgos (UBU)
Repositorio:Repositorio Institucional de la Universidad de Burgos (RIUBU)
OAI Identifier:oai:riubu.ubu.es:10259/3859
Acceso en línea:http://hdl.handle.net/10259/3859
Access Level:acceso abierto
Palabra clave:Automatic response
Clustering
Computational intelligence
Exploratory projection pursuit
k-means
Network intrusion detection
Informática
Computer science
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spelling Visualization and clustering for SNMP intrusion detectionSánchez, RaúlHerrero Cosío, ÁlvaroCorchado, EmilioAutomatic responseClusteringComputational intelligenceExploratory projection pursuitk-meansNetwork intrusion detectionInformáticaComputer scienceAccurate intrusion detection is still an open challenge. The present work aims at being one step toward that purpose by studying the combination of clustering and visualization techniques. To do that, the mobile visualization connectionist agent-based intrusion detection system (MOVICAB-IDS), previously proposed as a hybrid intelligent IDS based on visualization techniques, is upgraded by adding automatic response thanks to clustering methods. To check the validity of the proposed clustering extension, it has been applied to the identification of different anomalous situations related to the simple network management network protocol by using real-life data sets. Different ways of applying neural projection and clustering techniques are studied in the present article. Through the experimental validation it is shown that the proposed techniques could be compatible and consequently applied to a continuous network flow for intrusion detectionSpanish Ministry of Economy and Competitiveness with ref: TIN2010-21272-C02-01 (funded by the European Regional Development Fund) and SA405A12-2 from Junta de Castilla y Leon.Taylor & Francis201520152013info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttp://hdl.handle.net/10259/3859reponame:Repositorio Institucional de la Universidad de Burgos (RIUBU)instname:Universidad de Burgos (UBU)InglésCybernetics and Systems: An International Journal. 2013, V. 44, n. 6-7, p. 505-532http://dx.doi.org/10.1080/01969722.2013.803903info:eu-repo/grantAgreement/MINECO/TIN2010-21272-C02-01/info:eu-repo/grantAgreement/JCyL/SA405A12-2/info:eu-repo/semantics/openAccessoai:riubu.ubu.es:10259/38592026-05-28T07:56:11Z
dc.title.none.fl_str_mv Visualization and clustering for SNMP intrusion detection
title Visualization and clustering for SNMP intrusion detection
spellingShingle Visualization and clustering for SNMP intrusion detection
Sánchez, Raúl
Automatic response
Clustering
Computational intelligence
Exploratory projection pursuit
k-means
Network intrusion detection
Informática
Computer science
title_short Visualization and clustering for SNMP intrusion detection
title_full Visualization and clustering for SNMP intrusion detection
title_fullStr Visualization and clustering for SNMP intrusion detection
title_full_unstemmed Visualization and clustering for SNMP intrusion detection
title_sort Visualization and clustering for SNMP intrusion detection
dc.creator.none.fl_str_mv Sánchez, Raúl
Herrero Cosío, Álvaro
Corchado, Emilio
author Sánchez, Raúl
author_facet Sánchez, Raúl
Herrero Cosío, Álvaro
Corchado, Emilio
author_role author
author2 Herrero Cosío, Álvaro
Corchado, Emilio
author2_role author
author
dc.subject.none.fl_str_mv Automatic response
Clustering
Computational intelligence
Exploratory projection pursuit
k-means
Network intrusion detection
Informática
Computer science
topic Automatic response
Clustering
Computational intelligence
Exploratory projection pursuit
k-means
Network intrusion detection
Informática
Computer science
description Accurate intrusion detection is still an open challenge. The present work aims at being one step toward that purpose by studying the combination of clustering and visualization techniques. To do that, the mobile visualization connectionist agent-based intrusion detection system (MOVICAB-IDS), previously proposed as a hybrid intelligent IDS based on visualization techniques, is upgraded by adding automatic response thanks to clustering methods. To check the validity of the proposed clustering extension, it has been applied to the identification of different anomalous situations related to the simple network management network protocol by using real-life data sets. Different ways of applying neural projection and clustering techniques are studied in the present article. Through the experimental validation it is shown that the proposed techniques could be compatible and consequently applied to a continuous network flow for intrusion detection
publishDate 2013
dc.date.none.fl_str_mv 2013
2015
2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10259/3859
url http://hdl.handle.net/10259/3859
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Cybernetics and Systems: An International Journal. 2013, V. 44, n. 6-7, p. 505-532
http://dx.doi.org/10.1080/01969722.2013.803903
info:eu-repo/grantAgreement/MINECO/TIN2010-21272-C02-01/
info:eu-repo/grantAgreement/JCyL/SA405A12-2/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:Repositorio Institucional de la Universidad de Burgos (RIUBU)
instname:Universidad de Burgos (UBU)
instname_str Universidad de Burgos (UBU)
reponame_str Repositorio Institucional de la Universidad de Burgos (RIUBU)
collection Repositorio Institucional de la Universidad de Burgos (RIUBU)
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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