DETECTION OF PHISHING WEBSITES USING HYBRID MODEL
Abstract
Online technologies have revolutionized the modern computing world. There
are number of users who purchase products online and make payment through various
websites. There are multiple websites who ask user to provide sensitive data such as
username, password or credit card details etc. often for malicious reasons. This type of
website is known as phishing website. The phishing website can be detected based on some
important characteristics like URL (Uniform Resource Locator) and Domain identity.
Several approaches have been proposed for detection of phishing websites by extracting the
phishing data sets criteria to classify their legitimacy. However, there is no such approach
that can provide better results to the users from phishing attacks. This paper is an attempt
to contribute in that area by presenting a hybrid model for classification to detect phishing
websites with high accuracy and less error rate.
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