Abstract
Phishing is defined as developing a fake website similar as original to obtain users private information such as username, passwords and social security numbers. Now a days more number of research has been developed to identify fake websites but it has been done by original website owners based on user’s reviews. However still hacking users’ personal information’s is in active. Hence in this research we have proposed a new approach to identify fake websites from a huge number of websites that are available now is done by analyzing user’s reviews as primary factor and url identification. In url identification set of parameters and characteristics has been verified to identify whether uploaded new website has met our required needs if not then it considered to be phishing website. Second step is by keeping particular threshold value fake websites has been identified efficiently based on user’s reviews. The threshold value is designed as if same website obtained more number of bad reviews then it consider to be spam website. By implementing this two-step verification more number of phishing websites has been identified efficiently compared to existing approaches.
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