Phishing Website Detection using Natural Language Processing
E. Mariappan, C. Jean Celia Grace, Sundararaj Joe Patrick Gnanaraj, D. Elizabeth Paulsyah, Narayanaperumal Muthukumaran · 2024
Given the rapid proliferation of online services, there has been a corresponding uptick in nefarious activities aimed at misleading users into unintended actions. The internet, as a platform, has become a fertile ground for innovative methods employed by attackers, particularly the widespread menace of phishing. By leveraging counterfeit websites, malicious entities seek to unlawfully gather sensitive data including user information, login credentials, social security numbers, and financial particulars. Accurately distinguishing between a legitimate website and a phishing attempt presents a significant challenge. This research work introduces a model for analyzing phishing websites employing machine learning techniques. The model strives to forecast the authenticity of a website by utilizing a variety of classification Algorithms and features rooted in natural language processing (NLP).