Abstract
Phishing Websites steal confidential material like from digital users. They steal all information possible from an end user. They use different techniques to steal the data. Most of the internet users become victims across the globe due to lack of digital education. Most fake websites look like trusted and real websites. About 2.009 million Phishing websites are detected in 2020; this rises to 26.02 percent in 2021. Identity theft cases have doubled since early 2020. Normal users can't spot phishing sites. Detecting fake sites requires special tools. Detecting phishing websites used black-list/whitelist, knowledge, URL-based, visual-similarity, machine learning, heuristic methods. Models detect URL-analysis, Webpage code, Webpage text data, URL statistical data, website images, and content. This paper studied and reviewed Phishing website detection methods. Comparing models, techniques, and accuracy.
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