Identification of SPAM messages using an approach inspired on the immune system

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorGuzella, Thiago dos Santos-
Autor(es): dc.creatorSantos, Tomaz Aroldo Mota-
Autor(es): dc.creatorCaminhas, Walmir Matos-
Autor(es): dc.creatorUchôa, Joaquim Quinteiro-
Data de aceite: dc.date.accessioned2026-02-09T11:52:16Z-
Data de disponibilização: dc.date.available2026-02-09T11:52:16Z-
Data de envio: dc.date.issued2015-05-21-
Data de envio: dc.date.issued2015-05-21-
Data de envio: dc.date.issued2015-05-21-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/9645-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1149281-
Descrição: dc.descriptionIn this paper, an immune-inspired model, named innate and adaptive artificial immune system (IA-AIS) is proposed and applied to the problem of identification of unsolicited bulk e-mail messages (SPAM). It integrates entities analogous to macrophages, B and T lymphocytes, modeling both the innate and the adaptive immune systems. An implementation of the algorithm was capable of identifying more than 99% of legitimate or SPAM messages in particular parameter configurations. It was compared to an optimized version of the na¨ıve Bayes classifier, which has been attained extremely high correct classification rates. It has been concluded that IA-AIS has a greater ability to identify SPAM messages, although the identification of legitimate messages is not as high as that of the implemented na¨ıve Bayes classifier. © 2008 Elsevier Ireland Ltd. All rights reserved.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsacesso aberto-
???dc.source???: dc.sourceBiosystems, Volume 92, Issue 3, June 2008, Pages 215-225-
Palavras-chave: dc.subjectArtificial immune system-
Palavras-chave: dc.subjectSPAM identification-
Palavras-chave: dc.subjectContinuous learning-
Palavras-chave: dc.subjectInnate and adaptive immunity-
Palavras-chave: dc.subjectRegulatory t cells-
Título: dc.titleIdentification of SPAM messages using an approach inspired on the immune system-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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