Published Paper Details:

The project has been developed with the goal of enhancing online security by identifying and mitigating phishing threats. Phishing attacks have been identified as a major security concern, and traditional methods of detection have proven insufficient in handling sophisticated attacks. In this project, machine learning models have been employed to analyze URLs and classify them as either legitimate or phishing. Various features extracted from URLs, such as the presence of suspicious keywords, domain age, and the structure of the URL, have been considered for accurate classification. Datasets containing labeled URLs have been used for training and testing the models, with performance metrics evaluated to ensure optimal detection rates. The models have been optimized and validated using standard evaluation techniques, and their efficiency in real world scenarios has been demonstrated. By implementing this approach, the risks associated with phishing websites have been significantly reduced, and the reliability of the proposed solution has been confirmed