Kappa-fuzzy ARTMAP: A feature selection based methodology to intrusion detection in computer networks

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorFederal University of Mato Grosso-
Autor(es): dc.contributorFederal Institute of Mato Grosso-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorPurdue University-
Autor(es): dc.creatorAraujo, Nelcileno Virgilio De Souza-
Autor(es): dc.creatorOliveira, Ruy De-
Autor(es): dc.creatorFerreira, Edwilson Tavares-
Autor(es): dc.creatorNascimento, Valtemir Emerencio Do-
Autor(es): dc.creatorShinoda, Ailton Akira-
Autor(es): dc.creatorBhargava, Bharat-
Data de aceite: dc.date.accessioned2025-08-21T15:53:58Z-
Data de disponibilização: dc.date.available2025-08-21T15:53:58Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2013-12-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/TrustCom.2013.37-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/227540-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/227540-
Descrição: dc.descriptionIntrusions in computer networks have driven the development of various techniques for intrusion detection systems (IDSs). In general, the existing approaches seek two goals: high detection rate and low false alarm rate. The problem with such proposed solutions is that they are usually processing intensive due to the large size of the training set in place. We propose a technique that combines a fuzzy ARTMAP neural network with the well-known Kappa coefficient to perform feature selection. By adding the Kappa coefficient to the feature selection process, we managed to reduce the training set substantially. The evaluation results show that our proposal is capable of detecting intrusions with high accuracy rates while keeping the computational cost low. © 2013 IEEE.-
Descrição: dc.descriptionInstitute of Computing Federal University of Mato Grosso, Cuiabá, MT-
Descrição: dc.descriptionDepartment of Informatics Federal Institute of Mato Grosso, Cuiabá, MT-
Descrição: dc.descriptionDepartment of Electrical Engineering State University Júlio de Mesquita Filho, Ilha Solteira, SP-
Descrição: dc.descriptionDepartment of Computer Science Purdue University, West Lafayette, IN-
Descrição: dc.descriptionDepartment of Electrical Engineering State University Júlio de Mesquita Filho, Ilha Solteira, SP-
Formato: dc.format271-276-
Idioma: dc.languageen-
Relação: dc.relationProceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013-
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Palavras-chave: dc.subjectfeature selection-
Palavras-chave: dc.subjectFuzzy ARTMAP neural network-
Palavras-chave: dc.subjectintrusion detection-
Palavras-chave: dc.subjectKappa coefficient-
Título: dc.titleKappa-fuzzy ARTMAP: A feature selection based methodology to intrusion detection in computer networks-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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