Detecting Phishing URLs Using Machine Learning: A Review

The Internet’s explosive expansion has led many people to switch from conventional banking to online banking. Unfortunately, this transition has resulted in cybercrimes such as domain fraud, ransomware, hacking, social engineering, and phishing. Attackers easily use phishing websites to steal delicate personal data because of the Internet’s inherent anonymity, such as passwords and user identities. Deterring these phishing scams is critical for protecting online organisations and individual users. Therefore, the purpose of this study is to investigate and evaluate the current state of the art in detecting phishing URLs using machine learning. Various methods, including feature extraction methods and classification algorithms, were studied. The review discusses limitations and effectiveness evaluation metrics while providing possible improvements. This comprehensive review aims to provide insight into URL-based phishing detection techniques through machine-learning approaches, which promise more robust ways of enhancing online security against fraudulent activities.