EnLem: An Ensemble Learning-based Model for Detecting Phishing Websites

Abstract

<p>In this paper, there is a novel model based on ensemble learning for predicting phishing websites. The overall design is a combination of three individual machine-learning models with the help of the uni-variate feature selection model for detecting phishing and non-phishing URLs. The proposed model can minimize the error rate and provide improved accuracy with a short execution time. As compared with other traditional models, this model has higher performance metrics for detecting phishing websites compared with traditional machine learning and deep learning models. </p>