Open AccessReview Process on URL Phishing
Author(s) -
Vivek Sharma S,
R. Hemalatha,
Y B Kavyashree
Publication year - 2021
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/ijsrst218344
Subject(s) - phishing , naive bayes classifier , extreme learning machine , computer science , support vector machine , process (computing) , machine learning , artificial intelligence , computer security , world wide web , the internet , operating system , artificial neural network
Phishing is that the most typical and most dangerous attack among cybercrimes. The aim of these attacks is to steal the data that’s utilized by people and organizations to perform transactions or any vital info. The goal of this is often to perform an Extreme Learning Machine (ELM) primarily based upon the classification of options together with Phishing Websites information among the UC Irvine Machine Learning Repository information. For results assessment, ELM was compared with different machine learning (SVM), Naive Thomas Bayes (NB) strategies and detected to possess the best possible accuracy.