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ABSTRACT
With the increased usage of social media, mobile devices, and the internet in recent years, there has been a growing trend to move practically all real-world processes online, where computers and the internet are essential to every activity. The anonymity of the Internet causes many security breaches, though it simplifies our daily lives. One issue with internet security is phishing websites, which prey on both software and human vulnerabilities. It can be described as the act of luring online users so that one can obtain personal data, including usernames, passwords, and financial information. The first thing that needs to be investigated is how to identify distinct network threats. Phishing site URLs are used to gather sensitive data. In order to trick internet users and steal their personal information, phishers create websites that look and behave just like legitimate websites. The use of machine learning algorithms to identify phishing websites is discussed in detail in this research. The automated detection and classification of phishing websites by machine learning algorithms can greatly improve security measures.
