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Abstract：
In this paper, stylometric features, gender features and personality features are introduced in the phishing detection. Experimental results show that the detection accuracy reaches 95.05%, which is about 10% higher than that only using the stylometric features. This results indicates that the algorithm has detection effect. © 2019 IEEE.
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Year： 2019
Page： 450-456
Language： English
Cited Count：
WoS CC Cited Count： 0
SCOPUS Cited Count： 14
ESI Highly Cited Papers on the List： 0 Unfold All
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Chinese Cited Count：
30 Days PV： 12
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