Revealing non-alphabetical guises of spam-trigger vocables
Unsolicited bulk email (spam) nowadays accounts for nearly 75% of daily email traffic, a figure that speaks strongly for the need of finding better protection mechanisms against its dissemination. A clever trick recently exploited by email spammers in order to circumvent textual-based filters, invol...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | Colombia |
| Institución: | Universidad Nacional de Colombia |
| Repositorio: | Repositorio UN |
| Idioma: | español |
| OAI Identifier: | oai:repositorio.unal.edu.co:unal/42641 |
| Acceso en línea: | https://repositorio.unal.edu.co/handle/unal/42641 http://bdigital.unal.edu.co/32738/ |
| Access Level: | acceso abierto |
| Palabra clave: | Uncovering of spam vocables approximate string matching algorithm |
| Sumario: | Unsolicited bulk email (spam) nowadays accounts for nearly 75% of daily email traffic, a figure that speaks strongly for the need of finding better protection mechanisms against its dissemination. A clever trick recently exploited by email spammers in order to circumvent textual-based filters, involves obfuscation of black-listed words with visually equivalent text substitutions from non-alphabetic symbols, in such a way it still conveys the semantics of the original word to the human eye (e.g. masking viagra as v1@gr@ or as v-i-a-g-r-a). In this paper we discuss how a simple-yet-effective adaptation of a classical algorithm for string matching may meet this stylish challenge to effectively reveal the similarity between genuine spam-trigger terms with their disguised alpha-numeric variants. |
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