Detecting unwanted email using VAT

Islam, Md. Rafiqul and Chowdhury, Morshed U. 2011, Detecting unwanted email using VAT, in Software engineering, artificial intelligence, networking and parallel/distributed computing 2011, Springer, Berlin, Germany, pp.113-126.

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Title Detecting unwanted email using VAT
Author(s) Islam, Md. Rafiqul
Chowdhury, Morshed U.
Title of book Software engineering, artificial intelligence, networking and parallel/distributed computing 2011
Editor(s) Lee, Roger
Publication date 2011
Series Studies in computational intelligence ; v. 368
Chapter number 10
Total chapters 14
Start page 113
End page 126
Total pages 14
Publisher Springer
Place of Publication Berlin, Germany
Keyword(s) classification
email
FP
spam
TP
Summary Spam or unwanted email is one of the potential issues of Internet security and classifying user emails correctly from penetration of spam is an important research issue for anti-spam researchers. In this paper we present an effective and efficient spam classification technique using clustering approach to categorize the features. In our clustering technique we use VAT (Visual Assessment and clustering Tendency) approach into our training model to categorize the extracted features and then pass the information into classification engine. We have used WEKA (www.cs.waikato.ac.nz/ml/weka/) interface to classify the data using different classification algorithms, including tree-based classifiers, nearest neighbor algorithms, statistical algorithms and AdaBoosts. Our empirical performance shows that we can achieve detection rate over 97%.
ISBN 3642222889
9783642222887
ISSN 1860-949X
Language eng
Field of Research 080503 Networking and Communications
Socio Economic Objective 890206 Internet Hosting Services (incl. Application Hosting Services)
HERDC Research category B1 Book chapter
Copyright notice ©2011, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30043157

Document type: Book Chapter
Collection: School of Information Technology
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