Intelligent phishing detection scheme using deep learning algorithms

PurposePhishing attacks have evolved in recent years due to high-tech-enabled economic growth worldwide. The rise in all types of fraud loss in 2019 has been attributed to the increase in deception scams and impersonation, as well as to sophisticated online attacks such as phishing. The global impac...

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Veröffentlicht in:	Journal of enterprise information management Jg. 36; H. 3; S. 747 - 766
Hauptverfasser:	Adebowale, Moruf Akin, Lwin, Khin T., Hossain, M. A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bradford Emerald Publishing Limited 24.04.2023 Emerald Group Publishing Limited
Schlagworte:	Algorithms Artificial neural networks Averages Big Data Classification Classifiers Cybercrime Datasets Deception Deep learning Economic development Economic growth Electronic mail systems Frame design Fraud Identity theft Image classification Intelligence Internet Learning Machine learning Malware Model accuracy Natural language Neural networks Phishing Short term memory Software services Voice recognition Websites Deep learning Cybercrime Phishing detection Universal resource locator (URL) Big data Convolutional neural network (CNN) Long short-term memory (LSTM)
ISSN:	1741-0398, 1758-7409
Online-Zugang:	Volltext
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