Classification of Phishing Web Sites Features Based on Extreme Learning Machine

Abstract

Phishing are one of the most widely recognized and most perilous assaults among cybercrimes. The point of these assaults is to take the data utilized by people and associations to lead exchanges. Phishing sites contain different indications among their substance and internet browser-based data. The reason for this examination is to perform Extreme Learning Machine (ELM) based grouping for 30 highlights incorporating Phishing Websites Data in UC Irvine Machine Learning Repository database. For results evaluation, ELM was contrasted and other AI strategies, for example, Support Vector Machine (SVM), Naïve Bayes (NB) and identified to have the most noteworthy precision of 95.34%