Journal
CYBERNETICS AND SYSTEMS
Volume 44, Issue 6-7, Pages 533-549Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/01969722.2013.805110
Keywords
Bayesian filter; data compression; e-mail; S-tree; signatures; spam
Categories
Funding
- Grant Agency of the Czech Republic [P202/11/P142]
- European Regional Development Fund in the IT4Innovations Centre of Excellence project [CZ.1.05/1.1.00/02.0070]
- Bio-Inspired Methods: Research, development and knowledge transfer project [CZ.1.07/2.3.00/20.0073]
- Operational Programme Education for Competitiveness
- ESF
- state budget of the Czech Republic
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In this article, we introduce a novel method for spam detection based on a combination of Bayesian filtering, signature trees, and data compression-based similarity. Bayesian filtering is one of the most popular and most efficient algorithms for dealing with spam detection. The problem with Bayesian filtering is that it is unable to classify any e-mail without doubt and sometimes spam e-mails are classified as regular e-mails. This novel method sorts out this problem by using signature trees and data compression-based similarity. The main result of this article is an up to 99% improvement in spam detection precision using this novel method.
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