Navneet Yadav

AI-Based Phishing Detection: A Review and Practical Study

This paper presents a review and practical study of AI-based phishing detection. It explains how machine learning can be used to identify phishing websites using URL and webpage features. The paper discusses common machine learning models such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and Neural Networks. It also explains the main steps of building a phishing detection system, including data collection, preprocessing, feature extraction, model training, and evaluation. The paper discusses the challenges and limitations of machine-learning-based phishing detection and suggests areas for future work.