Using Machine Learning to Find Phishing Websites

Abstract

Phishing is one of the easiest ways to get delicate data from users who aren't doing anything wrong. The goal of phishing emails is to get important identities of users, pass codes, and bank statement data [1]. People who work in data protection nowadays are searching for reliable and consistent ways to find phishing sites. This article is about using ml algorithms to find phishing Websites. It does this by gathering and analysing different characteristics of both real and fake URLs. To find malicious urls, methodologies like Logistic Regression, Random Forest, as well as Support Vector Machine have been used. The aim of the research is to find phishing URLs and find the best machine learning technique [13] by making comparisons every method's overall accuracy, true positive rate, and negative predictive value.