Financial phishing detection method based on sensitive characteristics of webpage

Autor: Xiang-dong HU, Ke LIU, Feng ZHANG, Jia-fu LIN, Jun FU, Zhi-hui GUO
Jazyk: English<br />Chinese
Rok vydání: 2017
Předmět:
Zdroj: 网络与信息安全学报, Vol 3, Pp 31-38 (2017)
Druh dokumentu: article
ISSN: 2096-109X
DOI: 10.11959/j.issn.2096-109x.2017.00122
Popis: A financial phishing detection method based on sensitive characteristics of webpage was proposed, which acquired sensitive text information of specific hypertext markup language tags and computes sensitive text eigen-value. The method matches number of sensitive text using multiple pattern matching algorithm AC_SC (AC suitable for Chinese). Then, the method locates and cuts logo image of webpage, and utilizes PCA-SIFT algorithm to extract image features and match features with library of webpage logo which was established beforehand. Meanwhile, it calculates similarity of two logo image. Finally, the decision can be concluded by the text eigenvalue and image similarity. It shows that the method is better in pertinence and timeliness according to experiment, and achieves no less than 97% detection accuracy.
Databáze: Directory of Open Access Journals