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dc.contributor.authorHerrero Cosío, Álvaro
dc.contributor.authorNavarro, Martí
dc.contributor.authorCorchado Rodríguez, Emilio Santiago 
dc.contributor.authorJulián Inglada, Vicente
dc.date.accessioned2017-09-05T11:01:23Z
dc.date.available2017-09-05T11:01:23Z
dc.date.issued2013
dc.identifier.citationFuture Generation Computer Systems. Volumen 29 (1), pp. 250-261. Elsevier BV.
dc.identifier.issn0167-739X (Print)
dc.identifier.urihttp://hdl.handle.net/10366/134353
dc.description.abstractThis study presents a novel Hybrid Intelligent Intrusion Detection System (IDS) known as RT-MOVICAB-IDS that incorporates temporal control. One of its main goals is to facilitate real-time Intrusion Detection, as accurate and swift responses are crucial in this field, especially if automatic abortion mechanisms are running. The formulation of this hybrid IDS combines Artificial Neural Networks (ANN) and Case-Based Reasoning (CBR) within a Multi-Agent System (MAS) to detect intrusions in dynamic computer networks. Temporal restrictions are imposed on this IDS, in order to perform real/execution time processing and assure system response predictability. Therefore, a dynamic real-time multi-agent architecture for IDS is proposed in this study, allowing the addition of predictable agents (both reactive and deliberative). In particular, two of the deliberative agents deployed in this system incorporate temporal-bounded CBR. This upgraded CBR is based on an anytime approximation, which allows the adaptation of this Artificial Intelligence paradigm to real-time requirements. Experimental results using real data sets are presented which validate the performance of this novel hybrid IDS.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherElsevier BV
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleRT-MOVICAB-IDS: Addressing real-time intrusion detection
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported