Detection and classification techniques of SPAM
In this paper, we discussed techniques of detection, evaluation and classif cation of nonrequested eletronic messages massively sended (spam), with emphasis on the analysis technique that applied Artificial Inteligence (AI) and networks, which interacts, sharing informations about the origin of thes...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2008 |
| País: | Brasil |
| Institución: | Centro Universitário de Belo Horizonte (UNIBH) |
| Repositorio: | Revista e-xacta |
| Idioma: | portugués |
| OAI Identifier: | oai:ojs.periodicos.uninove.br:article/767 |
| Acceso en línea: | https://periodicos.uninove.br/exacta/article/view/767 |
| Access Level: | acceso abierto |
| Palabra clave: | Anti-spam. E-mail. Internet. |
| Sumario: | In this paper, we discussed techniques of detection, evaluation and classif cation of nonrequested eletronic messages massively sended (spam), with emphasis on the analysis technique that applied Artificial Inteligence (AI) and networks, which interacts, sharing informations about the origin of these emails through the internet. Three sceneries were used, in order to show a comparison among Baysean, Filter based on signatures, greylist and DNSBL techniques. |
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