Detection of URL-based Phishing Attacks Using Neural Networks

Abstract

Doing business in a network environment, despite its high efficiency, due to the fact that it is a "remote" activity, is very inspiring for various types of dishonest actions and fraud. Phishing is a form of fraud in which an attacker tries to find out sensitive information such as user login information or account information. The phishing attacks that are happening today are sophisticated and increasingly difficult to spot. To find out which URL is legitimate and which is not, we used a neural network as a binary classifier of machine learning. To measure the performance of the model, we used binary classification accuracy.