Abstract

Phishing is one of cybercrime's most widely perceived and risky ambushes. The aim of these attacks is to take the personal information and relationships used to organize trades. Phishing localities contain different signs within their information based on substance and web system. Extreme Learning Machine (ELM) based set for 30 features fusing Phishing Websites Data into UC Irvine Machine Learning Repository database is the reason behind this review. For the assessment of performance, ELM and other AI techniques, such as Support Vector Machine (SVM), Naïve Bayes (NB), were distinguished and considered to have the highest accuracy.