Securing the web: Machine learning's role in predicting and preventing phishing attacks

Website phishing is an evolving threat that poses significant risks to online users and organizations. This paper explores the application of machine learning techniques to detect phishing websites by analyzing key features such as URL structure, domain registration, and SSL/TLS certificates. Machine learning offers a dynamic, real-time approach to identifying phishing websites, providing enhanced accuracy and adaptability compared to traditional detection methods. By leveraging the ability of machine learning models to continuously learn and adapt to new phishing strategies, this research highlights the potential of these techniques to effectively combat emerging phishing threats. The paper also discusses future innovations, such as deep learning and natural language processing, which hold promise for further improving phishing detection systems and strengthening overall web security. These findings underscore the critical role of machine learning in safeguarding users from the growing threat of phishing websites.