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Real-Time Detection of Phishing Emails Using XG Boost Machine Learning Technique - Correction by Isaac Adom is a document available to read on EtoBox.

This study evaluates the effectiveness of four machine learning algorithms—Random Forest, Decision Tree, XGBoost, and Logistic Regression—in detecting phishing emails, finding that XGBoost outperforms the others in accuracy and precision. The research highlights the increasing sophistication of phishing attacks and the necessity for advanced detection methods, particularly those leveraging machine learning. The findings suggest that organizations can enhance their phishing detection capabilities by adopting

Author

Isaac Adom

Language

EN