Published Paper Details:

The proliferation in phishing attacks highlights the importance of strong cybersecurity protocols.. In this study, we present an innovative methodology that harnesses machine learning techniques to enhance the detection of phishing websites. Phishing attempts persist as a considerable risk to both individuals and organizations, underscoring the essential requirement for enhanced detection methods.. Leveraging the power of machine learning, our study outlines a systematic methodology for identifying phishing websites. We begin with a thorough data collection process, followed by preprocessing steps to refine the dataset. Feature extraction methods are then utilized to capture pertinent patterns suggestive of phishing endeavors. The core of our approach lies in the application of various machine learning algorithms for classification, enabling the automated identification of phishing websites. By conducting thorough tests and assessments, we showcase the efficiency and resilience of our detection system. By contributing to the advancement of cybersecurity measures, this research aims to empower users and organizations in combating phishing threats, thereby fostering a safer online environment.