Unmasking Phishing Threats through Cutting-Edge Machine Learning

Abstract

Website phishing has shown to be a serious security risk. Phishing is the starting point for many cyber attacks that compromise the confidentiality, integrity, and availability of customer and business data. Decades of effort have gone into developing innovative techniques for automatically recognizing phishing websites. Modern systems aren't very excellent at spotting fresh phishing attacks and require a lot of manual feature engineering, even though they can produce better outcomes. Thus, an open problem in this discipline is to identify tactics that can swiftly handle zero-day phishing attempts and automatically recognize phishing websites. The web page that is hosted at the given URL has a lotof information that can be utilized to assess the maliciousness of the web server. Machine Learning is a useful technique to identify. Here, we describe the characteristics of phishing domains, also known as fraudulent domains, what sets them apart from real domains, the significance of detecting these domains, and how machine learning may be used to detect them.