On Neural Networks and the Future of Spam
- Authors
-
-
A. C. Cosoi
University "Politehnica" Bucharest, Faculty of Automatic Control and Computer Science
-
M. S. Vlad
University "Politehnica" Bucharest, Faculty of Automatic Control and Computer Science
-
V. Sgarciu
University "Politehnica" Bucharest, Faculty of Automatic Control and Computer Science
-
- Abstract
- Content-based filters (e.g. Keyword Filters, Heuristics Filters, Statistical Learning Filters, Pattern Recognition Neural Networks, and so on) use tokens, which are found during message content analysis, to separate spam from legitimate messages. The effectiveness of these token-based filters is due to the presence of token signatures (e.g. tokens that are invariant for the many variants of spam messages). In our research, we discovered a new trend of spam messages that have a low frequency of token signatures, thus making them significantly more difficult to identify. Further on, we will describe this new type of spam and also suggest a few modalities to combat the spread of this prototype of the future spam trend.
- References
- Downloads
- Published
- 2008-06-30
- Issue
- Vol. 10 No. 2 (2008)
- Section
- Articles