Learning a deep neural network for predicting phishing website

Abstract

In recent years, we have seen a huge paradigm shift in business because of the fast development of the Web. For this reason, consumers change their tendency from customary shopping to the electronic business. In the time of electronic and versatile trade, huge quantities of money related exchanges are directed online on regular schedule, which created opportunities for new potential scheming chances. By utilizing the unknown structure of theWeb, attackers set out new procedures like phishing, to fool people with the utilization of false sites to gather their delicate data. It gather datas such as account IDs, usernames, passwords, credit card information and so on. In spite of the fact that organizations and software companies uses methodologies such as heuristics, visual and machine learning to prevent phishing attacks, still these can't keep the majority of the phishing assaults. In this paper, we evaluate the model by using LSTM technique by comparing it with previous studies and we will try to nd out the best features in LSTM.