文章基本信息

标题：Phishing Email Detection Based on Hybrid Features
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作者：Zhuorao Yang ; Chen Qiao ; Wanling Kan 等
期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2019
卷号：252
期号：4
页码：1-11
DOI：10.1088/1755-1315/252/4/042051
出版社：IOP Publishing
摘要：As an attack of social engineering, phishing email has caused tremendous financial loss to recipients. Therefore, there is an urgent need for phishing email detection with high accuracy. In this paper, we proposed phishing emails detection based on hybrid features. By analysing the email-header structure, email-URL information, email-script function and email psychological features, we extracted 18 hybrid features. Then we chose Support Vector Machine (SVM) classifier to evaluate our experiments. Experiments are performed on a dataset consisting of 500 legitimate emails and 500 phishing emails. The proposed approach achieved overall true-positive rate of 99%, false-positive rate of 9%, precision of 91.7% and accuracy of 95.00%. Furthermore, we evaluated the effectiveness of our proposed psychological features. The results showed that psychological features can improve the accuracy of detection and reduce the false-positive rate. Our proposed method has a good performance in detecting phishing emails.