Robust Ensemble Machine Learning Model for Filtering Phishing URLs: Expandable Random Gradient Stacked Voting Classifier (ERG-SVC)

Abstract

As cyber-attacks grow fast and complicated, the cybersecurity industry faces challenges to utilize state-of-the-art technology and strategies to battle the consistently present malicious threats. Phishing is a sort of social engineering attack produced technically and classified as identity theft and complicated attack vectors to steal information of internet users. In this perspective, our main objective of this study is to propose a unique, robust ensemble machine learning model architecture that provides the highest prediction accuracy with a low error rate while proposing few other robust machine learning models. Both supervised and unsupervised techniques were used for the detection pro..