Detection of fraudulent emails by employing advanced feature abundance

In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features are incorporat...

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Bibliographic Details

Published in:	Egyptian Informatics Journal
Main Authors:	Sarwat Nizamani, Nasrullah Memon, Mathies Glasdam, Dong Duong Nguyen
Format:	Article
Language:	English
Published:	Elsevier 2014-11-01
Subjects:	Classification CCM Feature set Fraudulent emails Spam emails
Online Access:	http://www.sciencedirect.com/science/article/pii/S1110866514000280