Buscar

 

RI UFLA (Universidade Federal de Lavras) >
DCC - Departamento de Ciência da Computação >
DCC - Artigos publicados em periódicos >

Por favor, utilize esse identificador para citar este item ou usar como link: http://repositorio.ufla.br/jspui/handle/1/9645

Título: Identification of SPAM messages using an approach inspired on the immune system
Autor(es): Guzella, Thiago dos Santos
Santos, Tomaz Aroldo Mota
Caminhas, Walmir Matos
Uchôa, Joaquim Quinteiro
Assunto: Artificial immune system
SPAM identification
Continuous learning
Innate and adaptive immunity
Regulatory t cells
Data de publicação: 21-Mai-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
Idioma: en
Aparece nas coleções: DCC - Artigos publicados em periódicos

Arquivos neste Item:

Arquivo Descrição TamanhoFormato
ARTIGO_Identification_of_SPAM_messages_using_an_approach_inspired_on_the_immune_system.pdf1,12 MBAdobe PDFVer/abrir

Itens protegidos por copyright, com todos os direitos reservados, Salvo indicação em contrário.


Mostrar estatísticas

 


DSpace Software Copyright © 2002-2007 MIT and Hewlett-Packard - Feedback