Abstract
The Spam filtering technique described here targets multiple recipient Spam messages with similar email addresses. We exploit these similar patterns to create a rule-based classification system (accuracy 92%). Our technique uses the ‘TO’ and ‘CC’ fields to classify an email as Spam or Legitimate. We introduce certain new rules which should enhance the performance of the current filtering techniques [1][4][5]. We also introduce a novel metric to calculate the degree of similarity between a set of strings.
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© 2005 Springer-Verlag Berlin Heidelberg
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Sharma, V., Sarda, P., Sharma, S. (2005). An Add-On to Rule-Based Sifters for Multi-recipient Spam Emails. In: Montoyo, A., Muńoz, R., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2005. Lecture Notes in Computer Science, vol 3513. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428817_37
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DOI: https://doi.org/10.1007/11428817_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26031-8
Online ISBN: 978-3-540-32110-1
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