Phishing Website Detection using Machine Learning: A Comprehensive Study

Abstract

Phishing attacks continue to be a serious danger to consumer privacy and internet safety. Attackers use false websites that look like authentic ones to steal sensitive data, including login credentials and financial information. In the study, different machine learning techniques for categorizing phishing websites are evaluated, including decision trees,logistic regression,Multinomial NB.This study also explores the potential integration of the generated models into online browsers and security systems, which would offer real-time defense against phishing assaults.The results of this study help to improve internet security, protect user data, and lessen the effect of phishing assaults on the digital world.