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Title:
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DATA MINING TECHNIQUES FOR SUSPICIOUS EMAIL DETECTION: A COMPARATIVE STUDY |
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Author(s):
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S.appavu Alias Balamurugan , R.rajaram , G.athiappan , M.muthupandian |
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ISBN:
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978-972-8924-40-9 |
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Editors:
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Jörg Roth, Jairo Gutiérrez and Ajith P. Abraham (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2007 |
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Edition:
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Single |
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Keywords:
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Data Mining, Decision Tree, Neural Network, Naïve Bayes, SVM, WEKA. |
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Type:
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Reflection Paper |
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First Page:
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213 |
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Last Page:
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217 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Email has become one of the fastest and most economical forms of communication. This paper proposes to apply
classification data mining for the task of suspicious email detection based on deception theory. In this paper, email data
was classified using four different classifiers (Neural Network, SVM, Naïve Bayesian and Decision Tree). The
experiment was performed using WEKA based on different features by which the email corpus is classified into
suspicious or normal emails. Experimental results show that simple ID3 classifier which make a binary tree, will give a
promising detection rates. |
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