Litcius/Paper detail

Research on Website Phishing Detection Based on LSTM RNN

Yang Su

20202020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)39 citationsDOI

Abstract

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.

Topics & Concepts

Computer scienceRecurrent neural networkPhishingArtificial intelligenceFeature extractionMachine learningFace (sociological concept)Artificial neural networkLong short term memoryDeep learningData miningSpeech recognitionThe InternetWorld Wide WebSocial scienceSociologySpam and Phishing DetectionNetwork Security and Intrusion DetectionSentiment Analysis and Opinion Mining