PHISHNET: Threat Intelligence System for Phishing Attacks Using Machine Learning

Phishing attacks pose a significant threat to cybersecurity by targeting individuals and organizations. This study introduces PHISHNET, a comprehensive threat intelligence system leveraging machine-learning (ML) techniques to detect and mitigate phishing attacks across URLs, emails, and SMS messages. The system utilizes Gradient Boosting for URL detection, achieving 98% accuracy, and Random Forest for email and SMS detection, achieving 97% and 96% accuracy, respectively. PHISHNET enhances phishing detection by analyzing key features, such as URL composition, email header information, and SMS content. The proposed approach ensures real-time detection and improves user security, making it a robust defense mechanism against phishing threats.