DETECTION OF PHISHING WEBSITES USING MACHINE LEARNING

Abstract

We know that the mobile devices have become so common, there is a trend toward moving practically all offline activity online. The simplest method for obtaining sensitive information from unwitting users is through phishing attacks. Phishers seek to get private data, including usernames, passwords, and bank account details. Cybersecurity experts are searching for consistent and dependable methods of detecting phishing websites. In this research, numerous properties of both genuine and phishing URLs are extracted and analyzed in order to detect phishing URLs. Phishing websites can be recognized using decision trees, random forests, and support vector machine algorithms. The results demonstrate the effectiveness of machine learning in proactively identifying phishing websites, thereby enhancing cybersecurity measures. learning, contributing to the overall improvement of online security and privacy.