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An innovative analyser for email classification based on grey list analysis

Islam, Md. Rafiqul and Zhou, Wanlei 2007, An innovative analyser for email classification based on grey list analysis, in 2007 IFIP International Conference on Network and Parallel Computing Workshops : proceedings : NPC 2007, 18-21 September, 2007, Dalian, China, IEEE Computer Society, Los Alimitos, Calif., pp. 176-182.

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Title An innovative analyser for email classification based on grey list analysis
Author(s) Islam, Md. Rafiqul
Zhou, Wanlei
Conference name NPC 2007 (2007 : Dalian, China)
Conference location Dalian, China
Conference dates 18-21 September 2007
Title of proceedings 2007 IFIP International Conference on Network and Parallel Computing Workshops : proceedings : NPC 2007, 18-21 September, 2007, Dalian, China
Editor(s) Li, Keqiu
Xiang, Yang
Jin, Hai
Qu, Wenyu
Cao, Zhiying
Publication date 2007
Conference series IFIP Conference on Network and Parallel Computing Workshops
Start page 176
End page 182
Publisher IEEE Computer Society
Place of publication Los Alimitos, Calif.
Keyword(s) email
TP
TN
spam
FP
GL
Summary In this paper we propose a new technique of email classification based on grey list (GL) analysis of user emails. This technique is based on the analysis of output emails of an integrated model which uses multiple classifiers of statistical learning algorithms. The GL is a list of classifier/(s) output which is/are not considered as true positive (TP) and true negative (TN) but in the middle of them. Many works have been done to filter spam from legitimate emails using classification algorithm and substantial performance has been achieved with some amount of false positive (FP) tradeoffs. In the case of spam detection the FP problem is unacceptable, sometimes. The proposed technique will provide a list of output emails, called "grey list (GL)", to the analyser for making decisions about the status of these emails. It has been shown that the performance of our proposed technique for email classification is much better compare to existing systems, in order to reducing FP problems and accuracy.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 0769529437
9780769529431
Language eng
Field of Research 080499 Data Format not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2007, IEEE.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30008180
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