Abstract
Abstract: In the landscape of cybersecurity, the relentless onslaughtof phishing attacks poses a persistent and multifaceted threat, exploiting vulnerabilities in human cognition to perpetrate crimes ranging from identity theft to financial fraud and data breaches. In response to this evolving menace, we present an innovative and robust Phishing Website Detection System that leverages cutting-edge machine learning techniques to fortify the digital defenses of individuals and organizations alike. Our system represents a culmination of research and development efforts aimed at creating a comprehensive solution capable of effectively identifying and thwarting phishing attempts across diverse online platforms. By integrating a multitude of features spanning URL structure analysis, content-based attributes, SSL certificate characteristics, and user interaction patterns, our system adopts a multifaceted approach to phishing detection, enabling it to discern between legitimate and malicious websites with unparalleled accuracy.
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