Abstract:
Phishing is a type of social engineering attack often used to steal user data. Especially in e-banking
attackers sent an email that appears legitimate but is actually meant to lure a potential victim into
providing some level of personal information for nefarious purpose, including login credentials and
credit card numbers. In this paper we employ four data mining classification algorithms to detect the
phishing emails in e-banking and then we use the weighted majority vote ensemble method to improve
the detection of phishing emails and compare the performance of each. Experimental results shows that
decision tree builds the best classifier.
