Published Paper Details:

SafeSurf is an innovative phishing detection system that identifies and classifies phishing URLs and emails through cutting-edge machine learning techniques. Its primary goal is to enhance online security by utilizing robust classification algorithms, such as Random Forest and Naive Bayes, to evaluate the legitimacy of URLs and email content. The system's foundation lies in analyzing various features, including URL structure, domain names, the presence of suspicious keywords, email metadata, and the content of emails to detect phishing attempts. By conducting this analysis, SafeSurf can effectively differentiate between legitimate and malicious links or emails, providing real-time protection against phishing threats. The project also incorporates web scraping capabilities, enabling the system to continuously collect fresh data from the internet to update its database of phishing indicators. Furthermore, SafeSurf features real-time monitoring to identify phishing attempts as they arise