URL BASED PHISHING DETECTION

Phishing attacks pose a significant threat to online security, targeting individuals and organizations with deceptive emails and websites designed to steal sensitive information. Traditional methods of detecting phishing websites have become inadequate against the evolving tactics employed by cybercriminals. This study explores the application of machine learning techniques in phishing website detection, aiming to enhance accuracy and real-time response capabilities. The results highlight the significance of this research in strengthening online security. By leveraging machine learning techniques, the proposed system provides a proactive defense against phishing attacks, safeguarding users, businesses, and organizations from financial losses, identity theft, and reputational damage. Furthermore, the study underscores the importance of continuous research and collaboration in the ever-changing landscape of cybersecurity, ensuring a safer digital environment for all.