A domain-feature enhanced classification model for the detection of Chinese phishing e-Business websites

  • Zhang, Dongsong; 
  • Yan, Zhijun; 
  • Jiang, Hansi; 
  • Kim, Taeha
Citations

WEB OF SCIENCE

48
Citations

SCOPUS

64

초록

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.

키워드

Phishing websites; E-business; Classification; Detection; Feature vectors
제목
A domain-feature enhanced classification model for the detection of Chinese phishing e-Business websites
저자
Zhang, Dongsong; Yan, Zhijun; Jiang, Hansi; Kim, Taeha
DOI
10.1016/j.im.2014.08.003
발행일
2014-11
유형
Article
저널명
Information and Management
권
51
호
7
페이지
845 ~ 853