INNOVATE A MODEL OF PHISHING WEBSITE AND DETECTION WITH FEATURES TOOL

The phishing email is one of the significant threats in the world today and has caused tremendous financial losses. Although the methods of confrontation are continually being updated, the results of those methods are not very satisfactory at present. Moreover, phishing emails are growing at an alarming rate in recent years. Therefore, more effective phishing detection technology is needed to limit the threat of phishing emails. In this article, we first analysed the structure of the email Then, based on an improved Recurrent Convolution Neural Network (RCNN) model with multilevel vectors and attention mechanisms, we proposed a new named phishing email detection model, to be used to model emails at the subject level, email body level, character level, and word level at the same time. To evaluate its effectiveness, we use an unbalanced dataset that presents the actual ratio of phishing emails to legitimate emails. Experimental results show. Meanwhile, the ensure that the filter can identify phishing emails with high probability and filter out legitimate emails as little as possible. This promising result is superior to the existing detection methods and verifies the effectiveness of in detecting phish.