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

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... . 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.