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Open AccessFeature PaperArticle

A Deep-Learning-Driven Light-Weight Phishing Detection Sensor

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Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
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School of Sino-Dutch Biomedical & Information Engineering, Northeastern University, Shenyang 110169, China
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Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang 110169, China
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Automation College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(19), 4258; https://doi.org/10.3390/s19194258
Received: 10 September 2019 / Revised: 25 September 2019 / Accepted: 28 September 2019 / Published: 30 September 2019
(This article belongs to the Special Issue Sensor Signal and Information Processing II)
This paper designs an accurate and low-cost phishing detection sensor by exploring deep learning techniques. Phishing is a very common social engineering technique. The attackers try to deceive online users by mimicking a uniform resource locator (URL) and a webpage. Traditionally, phishing detection is largely based on manual reports from users. Machine learning techniques have recently been introduced for phishing detection. With the recent rapid development of deep learning techniques, many deep-learning-based recognition methods have also been explored to improve classification performance. This paper proposes a light-weight deep learning algorithm to detect the malicious URLs and enable a real-time and energy-saving phishing detection sensor. Experimental tests and comparisons have been conducted to verify the efficacy of the proposed method. According to the experiments, the true detection rate has been improved. This paper has also verified that the proposed method can run in an energy-saving embedded single board computer in real-time. View Full-Text
Keywords: phishing detection; cyber security; deep learning phishing detection; cyber security; deep learning
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Wei, B.; Hamad, R.A.; Yang, L.; He, X.; Wang, H.; Gao, B.; Woo, W.L. A Deep-Learning-Driven Light-Weight Phishing Detection Sensor. Sensors 2019, 19, 4258.

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