PHISHING EMAIL DETECTOR USING MACHINE LEARNING AND NLP

Abstract

Email Spam Detection Using Machine Learning Algorithms is an intelligent cybersecurity and communication filtering system developed to identify and classify spam emails using machine learning and data analysis techniques. The primary objective of the system is to improve email security and communication efficiency by automatically detecting unwanted, fraudulent, phishing, and malicious emails through artificial intelligence technologies. In modern digital communication environments, emails are widely used for business communication, online services, marketing, banking, education, and information exchange. However, the rapid growth of email usage has also increased the number of spam emails, phishing attacks, promotional messages, malware attachments, and fraudulent communications that threaten user privacy and cybersecurity. Traditional spam filtering methods mainly rely on rule-based filtering, blacklists, keyword matching, and manual analysis techniques, which may fail to detect new spam patterns and evolving phishing attacks effectively. The proposed system utilizes email datasets containing email content, sender information, subject lines, hyperlinks, message frequency, and text features to train machine learning models capable of identifying spam emails accurately. Data preprocessing operations such as text cleaning, tokenization, stop-word removal, stemming, feature extraction, and vectorization are performed to improve dataset quality and classification performance. Various machine learning algorithms including Naive Bayes, Support Vector Machine, Decision Tree, Random Forest, and Logistic Regression are implemented to classify emails as spam or legitimate messages based on textual and behavioral analysis. The trained machine learning models analyze incoming emails in real time and generate automated spam detection results for improving communication security and email management. The proposed Email Spam Detection Using Machine Learning Algorithms system improves spam classification accuracy, reduces phishing risks, enhances email security, and supports intelligent communication filtering using artificial intelligence and machine learning technologies