Hybrid feature selection for phishing email detection
Hamid, Isredza Rahmi A. and Abawajy, Jemal 2011, Hybrid feature selection for phishing email detection, in Algorithms and architectures for parallel processing, Springer, Berlin, Germany, pp.266-275.
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Title
Hybrid feature selection for phishing email detection
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. Through an analysis of a number of phishing and ham email collected, this paper focused on fundamental attacker behavior which could be extracted from email header. It also put forward a hybrid feature selection approach based on combination of content-based and behavior-based. The approach could mine the attacker behavior based on email header. On a publicly available test corpus, our hybrid features selections are able to achieve 96% accuracy rate. In addition, we successfully tested the quality of our proposed behavior-based feature using the information gain.
ISBN
9783642246494
ISSN
0302-9743 1611-3349
Language
eng
Field of Research
080501 Distributed and Grid Systems
Socio Economic Objective
890206 Internet Hosting Services (incl. Application Hosting Services)