A Genetic Algorithm Based Model for Chinese Phishing E-commerce Websites Detection

被引：0

作者：

Yan, Zhijun ^{[1
]}

Liu, Su ^{[1
]}

Wang, Tianmei ^{[2
]}

Sun, Baowen ^{[2
]}

Jiang, Hansi ^{[1
]}

Yang, Hangzhou ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Management & Econ, Beijing, Peoples R China

[2] Cent Univ Finance & Econ, Sch Informat, Beijing, Peoples R China

来源：

HCI IN BUSINESS, GOVERNMENT, AND ORGANIZATIONS: ECOMMERCE AND INNOVATION, PT I | 2016年 / 9751卷

关键词：

Chinese phishing website detection; E-commerce; Sequential minimal optimization; Genetic algorithm;

D O I：

10.1007/978-3-319-39396-4_25

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We propose a new Chinese phishing e-commerce websites detection model which integrates the URL features and web features of websites. Some unique features of Chinese e-Commerce websites are included and Sequential Minimal Optimization (SMO) algorithm is applied to identify the phishing e-commerce websites. At the same time, we adopt the genetic algorithm (GA) to optimize the detection model. The evaluation results show that the performance of SMO algorithm is better than the baseline model and GA improves the detection accuracy significantly.

引用

页码：270 / 279

页数：10

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