DocumentCode :
2420353
Title :
On neural networks and the future of spam
Author :
Cosoi, A.C. ; Vlad, M.S. ; Sgarciu, V.
Author_Institution :
Fac. of Autom. Control & Comput. Sci., Univ. Politeh. Bucharest, Bucharest
Volume :
3
fYear :
2008
fDate :
22-25 May 2008
Firstpage :
230
Lastpage :
233
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.
Keywords :
information filters; neural nets; unsolicited e-mail; content-based filters; heuristics filters; legitimate messages; message content analysis; pattern recognition neural networks; statistical learning filters; Automatic control; Bayesian methods; Computer science; Databases; Frequency; Information filtering; Information filters; Neural networks; Statistical learning; Unsolicited electronic mail;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation, Quality and Testing, Robotics, 2008. AQTR 2008. IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4244-2576-1
Electronic_ISBN :
978-1-4244-2577-8
Type :
conf
DOI :
10.1109/AQTR.2008.4588917
Filename :
4588917
Link To Document :
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