Turkish Journal of Electrical Engineering and Computer Sciences




Phishing websites are fake ones that are developed by ill-intentioned people to imitate real and legal websites. Most of these types of web pages have high visual similarities to hustle the victims. The victims of phishing websites may give their bank accounts, passwords, credit card numbers, and other important information to the designers and owners of phishing websites. The increasing number of phishing websites has become a great challenge in e-business in general and in electronic banking specifically. In the present study, a novel framework based on model-based clustering is introduced to fight against phishing websites. First, a model is developed out of those websites that already have been identified as phishing websites as well as real websites that belong to the original owners. Then each new website is compared with the model and categorized into one of the model clusters by a probability. The analyses reveal that the proposed algorithm has high accuracy.


Phishing, clustering, banking website, data mining, security

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