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dc.contributor.authorPerona Balda, Iñigo ORCID
dc.contributor.authorGurrutxaga Goikoetxea, Ibai ORCID
dc.contributor.authorArbelaiz Gallego, Olatz ORCID
dc.contributor.authorMartín Aramburu, Jose Ignacio
dc.contributor.authorMuguerza Rivero, Javier Francisco
dc.contributor.authorPérez de la Fuente, Jesús María ORCID
dc.date.accessioned2025-01-14T18:08:42Z
dc.date.available2025-01-14T18:08:42Z
dc.date.issued2008-11-27
dc.identifier.citationData Mining & Analytics 2008: Procedings of the 7th Australasian Data Mining Conference (AusDM 2008) 87 : 171-178 (2008es_ES
dc.identifier.isbn978-1-920682-68-2
dc.identifier.urihttp://hdl.handle.net/10810/71399
dc.description.abstractThe popularity of computer networks broadens the scope for network attackers and increases the damage these attacks can cause. In this context, Intrusion Detection Systems (IDS) are included as part of any complete security package. This work focuses on nIDSs which work by scanning the network traffic. A service-independent payload processing approach is presented to increase detection rates in non-flood attacks. Three different techniques for payload processing are proposed and they are shown to be able to efficiently detect some of the attack types. Moreover, the proper integration of the knowledge of the different techniques, payload-based and packet header-based, always improves the results. This work leads us to conclude that payload analysis can be used in a general manner, with no service- or port-specific modelling, to detect attacks in network traffic.es_ES
dc.description.sponsorshipThis work was partly funded by the Diputación Foral de Gipuzkoa and the European Union.es_ES
dc.language.isoenges_ES
dc.publisherACMes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectIntrusion detection systemses_ES
dc.subjectunsupervised anomaly detectiones_ES
dc.subjectpayloades_ES
dc.titleService-independent payload analysis to improve intrusion detection in network traffices_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.holder© 2008, Australian Computer Society published in association with the ACMes_ES
dc.relation.publisherversionhttps://dl.acm.org/doi/10.5555/2449288.2449315es_ES
dc.identifier.doi10.5555/2449288.2449315
dc.departamentoesCiencia de la computación e inteligencia artificiales_ES
dc.departamentoeuKonputagailuen Arkitektura eta Teknologiaes_ES


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