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Using feature selection and classification scheme for automating phishing email detection


Hamid, IRA and Abawajy, J and Kim, T-H, Using feature selection and classification scheme for automating phishing email detection, Studies in Informatics and Control, 22, (1) pp. 61-70. ISSN 1220-1766 (2013) [Refereed Article]


Copyright Statement

Copyright 2013 National Institute for Research & Development in Informatics

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DOI: doi:10.24846/v22i1y201307


Email has become the critical communication medium for most organizations. Unfortunately, email-born attacks in computer networks are causing considerable economic losses worldwide. Exiting phishing email blocking appliances have little effect in weeding out the vast majority of phishing emails. At the same time, online criminals are becoming more dangerous and sophisticated. Phishing emails are more active than ever before and putting the average computer user and organizations at risk of significant data, brand and financial loss. In this paper, we propose a hybrid feature selection approach based on combination of content-based and behaviour-based. The approach could mine the attacker behaviour based on email header. On a publicly available test corpus, our hybrid features selection is able to achieve 94% accuracy rate.

Item Details

Item Type:Refereed Article
Keywords:internet security, behavior-based, feature selection, phishing
Research Division:Information and Computing Sciences
Research Group:Cybersecurity and privacy
Research Field:Cybersecurity and privacy not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Communication technologies, systems and services
Objective Field:Communication technologies, systems and services not elsewhere classified
UTAS Author:Kim, T-H (Dr Tai Kim)
ID Code:89271
Year Published:2013
Web of Science® Times Cited:18
Deposited By:Information and Communication Technology
Deposited On:2014-02-27
Last Modified:2018-03-27
Downloads:706 View Download Statistics

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