Deakin home > Deakin University Library > Deakin Research Online > Multi-classifier classification of spam email on an ubiquitous multi-core architecture
Openly accessible

Multi-classifier classification of spam email on an ubiquitous multi-core architecture

Islam, Md. Rafiqul, Singh, Jaipal, Chonka, Ashley and Zhou, Wanlei 2008, Multi-classifier classification of spam email on an ubiquitous multi-core architecture, in IFIP NPC 2008 : 2008 IFIP International Conference on Network and Parallel Computing Workshops : proceedings, 18-21 October, 2008, Shanghai, China, IEEE Computer Society, Los Alamitos, Calif., pp. 210-217.

Attached Files (Some files may be inaccessible until you login with your Deakin Research Online credentials)
Name Description MIMEType Size Downloads
islam-multiclassifier-2008.pdf Published version application/pdf 358.24KB 143

Title Multi-classifier classification of spam email on an ubiquitous multi-core architecture
Author(s) Islam, Md. Rafiqul
Singh, Jaipal
Chonka, Ashley
Zhou, Wanlei
Conference name International Conference on Network and Parallel Computing (2008 : Shanghai, China)
Conference location Shanghai, China
Conference dates 18-21 October 2008
Title of proceedings IFIP NPC 2008 : 2008 IFIP International Conference on Network and Parallel Computing Workshops : proceedings, 18-21 October, 2008, Shanghai, China
Editor(s) Cao, Jian
Publication date 2008
Conference series International Conference on Network and Parallel Computing
Start page 210
End page 217
Total pages xxvi, 594 p.
Publisher IEEE Computer Society
Place of publication Los Alamitos, Calif.
Summary This paper presents an innovative fusion based multi-classifier email classification on a ubiquitous multi-core architecture. Many approaches use text-based single classifiers or multiple weakly trained classifiers to identify spam messages from a large email corpus. We build upon our previous work on multi-core by apply our ubiquitous multi-core framework to run our fusion based multi-classifier architecture. By running each classifier process in parallel within their dedicated core, we greatly improve the performance of our proposed multi-classifier based filtering system. Our proposed architecture also provides a safeguard of user mailbox from different malicious attacks. Our experimental results show that we achieved an average of 30% speedup at the average cost of 1.4 ms. We also reduced the instance of false positive, which is one of the key challenges in spam filtering system, and increases email classification accuracy substantially compared with single classification techniques.
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 9780769533544
076953354X
Language eng
Field of Research 080303 Computer System Security
080302 Computer System Architecture
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2008, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30025743

Document type: Conference Paper
Collections: School of Engineering and Information Technology
Open Access Collection
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in Deakin Research Online is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 2 times in Scopus
Access Statistics: 366 Abstract Views, 143 File Downloads  -  Detailed Statistics
Created: Thu, 25 Mar 2010, 14:56:45 EST