Виявлення фішингових сайтів за допомогою машинного навчання

Abstract

Phishing attacks are constantly increasing on the internet today. Fraudsters create fake websites imitating banking and payment services in order to obtain users' confidential data. But machine learning can help detect phishing websites faster and more effectively. This paper examines classifiers used to identify new, unlisted threats: Random Forest, XGBoost, and Support Vector Machines (SVM)