A Secure NLP-Based Webmail System for Spam Detection, Phishing Prevention, and Contextual Search

Abstract

With the increasing use of digital communication, it's important to have a secure and efficient email system. This project focuses on developing a webmail system that helps filter out spam, detect phishing attempts, and improve search accuracy using Natural Language Processing (NLP). The system uses the Naïve Bayes Classifier to analyze emails, identifying and blocking messages that contain suspicious or harmful keywords. Any flagged emails are reviewed by an administrator to track potential threats. Additionally, the system prevents users from accessing harmful links and phishing attempts, ensuring data security. It also enhances the search process by understanding the context of queries, making it easier to find relevant messages. By applying feature selection, pattern analysis, and classification techniques, this project aims to provide a safer and more effective communication platform while reducing exposure to spam and cyber threats.