Comparison of Machine Learning Algorithms Used for Phishing Detection

The purpose of this article is to contribute to the improvement of organizational management regarding the prevention, detection, and disproof of phishing attacks using artificial intelligence. Therefore, we conducted a comparative study based on results obtained from two scientific papers, using the same dataset. In this article, to detect phishing, we analyzed the performance of three machine learning algorithms: Logistic Regression, Decision Tree, and Random Forest. Our results demonstrate that the Random Forest model is highly effective in correctly identifying phishing websites while minimizing the number of legitimate websites misclassified as phishing.