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A domain-feature enhanced classification model for the detection of Chinese phishing e-Business websites
- Authors
- Zhang, Dongsong; Yan, Zhijun; Jiang, Hansi; Kim, Taeha
- Issue Date
- Nov-2014
- Publisher
- ELSEVIER SCIENCE BV
- Keywords
- Phishing websites; E-business; Classification; Detection; Feature vectors
- Citation
- INFORMATION & MANAGEMENT, v.51, no.7, pp 845 - 853
- Pages
- 9
- Journal Title
- INFORMATION & MANAGEMENT
- Volume
- 51
- Number
- 7
- Start Page
- 845
- End Page
- 853
- ISSN
- 0378-7206
1872-7530
- Abstract
- We propose a novel classification model that consists of features of website URLs and content for automatically detecting Chinese phishing e-Business websites. The model incorporates several unique domain-specific features of Chinese e-Business websites. We evaluated the proposed model using four different classification algorithms and approximately 3,000 Chinese e-Business websites. The results show that the Sequential Minimal Optimization (SMO) algorithm performs the best. The proposed model outperforms two baseline models in detection precision, recall, and F-measure. The results of a sensitivity analysis demonstrate that domain-specific features have the most significant impact on the detection of Chinese phishing e-Business websites. (C) 2014 Elsevier B.V. All rights reserved.
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