Research on Website Phishing Detection Based on LSTM RNN
Yang Su · 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) · 2020
In order to effectively detect phishing attacks, this paper designed a new detection system for phishing websites using LSTM Recurrent Neural Networks (RNN). LSTM has the advantage of capturing data timing and long-term dependencies. LSTM has strong learning ability, can automatically learn data characterization without manual extraction of complex features, and has strong potential in the face of complex high-dimensional massive data. Experimental results show that this model approach the accuracy of 99.1%, is higher than that of other neural network algorithms.