Phishing Email Detection Using Machine Learning and Natural Language Processing
In today’s digital age, emails serve as a crucial communication medium. However, they are often exploited by malicious users to send phishing emails, which are fraudulent attempts to steal sensitive information like login credentials and financial details. While traditional methods for phishing detection rely heavily on user vigilance, this paper proposes a more automated approach using Machine Learning techniques. Existing systems that use methods like Support Vector Classifier (SVC) require human intervention, whereas the proposed system leverages Random Forest and XGBoost for more accurate and efficient phishing detection. The proposed model achieved high accuracy, demonstrating its potential as a robust solution for phishing email detection.
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