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

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conference contribution
posted on 2008-01-01, 00:00 authored by MD Rafiqul Islam, J Singh, Ashley Chonka, Wanlei Zhou
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.



International Conference on Network and Parallel Computing (2008 : Shanghai, China)


210 - 217


IEEE Computer Society


Shanghai, China

Place of publication

Los Alamitos, Calif.

Start date


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Publication classification

E1.1 Full written paper - refereed

Copyright notice

2008, IEEE


J Cao

Title of proceedings

IFIP NPC 2008 : 2008 IFIP International Conference on Network and Parallel Computing Workshops : proceedings, 18-21 October, 2008, Shanghai, China