Review Paper Real-Time Phishing Website With Machine Learning

Phishing is a cybercrime in which an attacker sends a false email designed to mislead the receiver into exposing personal information, such as passwords, credit card numbers, or other sensitive data. Phishing websites are one of the most frequent ways attackers carry out phishing attacks. These websites are made to look like actual websites, such as banking websites or online businesses, to fool the victim into entering their personal information. Machine learning is a form of artificial intelligence that can detect phishing websites. Machine learning algorithms can be educated on enormous datasets of phishing websites and legal websites to identify the properties that discriminate between the two. Once taught, these algorithms can be used to classify new websites as phishing or authentic in real time. This paper addresses the state-of-the-art in machine learning-based phishing website identification. The paper explains the many machine-learning approaches that have been deployed for this work, as well as the features that have been utilized to train these algorithms. The article also explores the limitations of real-time phishing website identification and the prospects of this research.