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Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/9645

Title: Identification of SPAM messages using an approach inspired on the immune system
???metadata.dc.creator???: Guzella, Thiago dos Santos
Santos, Tomaz Aroldo Mota
Caminhas, Walmir Matos
Uchôa, Joaquim Quinteiro
Keywords: Artificial immune system
SPAM identification
Continuous learning
Innate and adaptive immunity
Regulatory t cells
Issue Date: 21-May-2015
Abstract: In 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.
URI: http://repositorio.ufla.br/jspui/handle/1/9645
???metadata.dc.language???: en
Appears in Collections:DCC - Artigos publicados em periódicos

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