Phishing detection method based on URL features

被引：5

作者：

机构：

[1] School of Computer Science and Engineering, Southeast University

[2] Key Laboratory of Computer Network and Information Integration of Ministry of Education, Southeast University

[3] Jiangsu Provincial Key Laboratory of E-Business, Nanjing University of Finance and Economics

来源：

Cao, J. (jx.cao@seu.edu.cn) | 1600年 / Southeast University卷 / 29期

关键词：

Incremental learning; Phishing detection; Support vector machine; Uniform resource locator (URL) features;

D O I：

10.3969/j.issn.1003-7985.2013.02.005

中图分类号：

学科分类号：

摘要：

In order to effectively detect malicious phishing behaviors, a phishing detection method based on the uniform resource locator (URL) features is proposed. First, the method compares the phishing URLs with legal ones to extract the features of phishing URLs. Then a machine learning algorithm is applied to obtain the URL classification model from the sample data set training. In order to adapt to the change of a phishing URL, the classification model should be constantly updated according to the new samples. So, an incremental learning algorithm based on the feedback of the original sample data set is designed. The experiments verify that the combination of the URL features extracted in this paper and the support vector machine (SVM) classification algorithm can achieve a high phishing detection accuracy, and the incremental learning algorithm is also effective. © Copy Right.

引用

页码：134 / 138

页数：4

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