Phishing Email Detection Based on Hybrid Features

2018 4th International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Yang, Zhuorao^1 ; Qiao, Chen^1 ; Kan, Wanling^1 ; Qiu, Junji^1

School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China^1

关键词: E-mail headers;    Email Detection;    False positive rates;    Financial loss;    Hybrid features;    Psychological features;    Social engineering;    True positive rates;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/252/4/042051/pdf
DOI  :  10.1088/1755-1315/252/4/042051

来源: IOP

【 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.