Title :
Learn to Detect Phishing Scams Using Learning and Ensemble ?Methods
Author :
Saberi, Alireza ; Vahidi, Mojtaba ; Bidgoli, Behrouz Minaei
Author_Institution :
Iran Univ. of Sci. & Technol., Tehran
Abstract :
Phishing attack is a kind of identity theft which tries to steal confidential data like on-line bank account information. In a phishing attack scenario, attacker deceives users by a fake email which is called scam. In this paper we employ three different learning methods to detect phishing scams. Then, we use ensemble methods on their results to improve our scam detection mechanism. Experimental results show that the proposed method can detect 94.4% of scam emails correctly, while only 0.08% of legitimate emails are classified as scams.
Keywords :
computer crime; confidential data; ensemble methods; fake email; identity theft; learning; phishing scams; Computer crime; Conferences; Data engineering; Data mining; Electronic mail; Intelligent agent; Internet; Learning systems; Uniform resource locators; Unsolicited electronic mail; Lerning MethodsPhishingScamSpam.;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology Workshops, 2007 IEEE/WIC/ACM International Conferences on
Conference_Location :
Silicon Valley, CA
Print_ISBN :
0-7695-3028-1
DOI :
10.1109/WI-IATW.2007.79