MVGL analyser for multi-classifier based spam filtering system

Islam, Md Rafiqul, Zhou, Wanlei and Chowdhury, Morshed U 2009, MVGL analyser for multi-classifier based spam filtering system, in ICIS 2009 : Proceedings of the 8th IEEE/ACIS International Conference on Computer and Information Science 2009, IEEE, Piscataway, N. J., pp. 394-399.

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Title MVGL analyser for multi-classifier based spam filtering system
Author(s) Islam, Md Rafiqul
Zhou, Wanlei
Chowdhury, Morshed U
Conference name Computer and Information Science. Conference (8th : 2009 : Shanghai, China)
Conference location Shanghai, China
Conference dates 1-3 Jun. 2009
Title of proceedings ICIS 2009 : Proceedings of the 8th IEEE/ACIS International Conference on Computer and Information Science 2009
Publication date 2009
Start page 394
End page 399
Publisher IEEE
Place of publication Piscataway, N. J.
Summary In the last decade, the rapid growth of the Internet and email, there has been a dramatic growth in spam. Spam is commonly defined as unsolicited email messages and protecting email from the infiltration of spam is an important research issue. Classifications algorithms have been successfully used to filter spam, but with a certain amount of false positive trade-offs, which is unacceptable to users sometimes. This paper presents an approach to overcome the burden of GL (grey list) analyzer as further refinements to our multi-classifier based classification model (Islam, M. and W. Zhou 2007). In this approach, we introduce a ldquomajority voting grey list (MVGL)rdquo analyzing technique which will analyze the generated GL emails by using the majority voting (MV) algorithm. We have presented two different variations of the MV system, one is simple MV (SMV) and other is the ranked MV (RMV). Our empirical evidence proofs the improvements of this approach compared to the existing GL analyzer of multi-classifier based spam filtering process.
ISBN 9780769536415
Language eng
Field of Research 080105 Expert Systems
Socio Economic Objective 810107 National Security
HERDC Research category E2 Full written paper - non-refereed / Abstract reviewed
Copyright notice ©2009, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30029158

Document type: Conference Paper
Collection: School of Information Technology
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