A stacking model using URL and HTML features for phishing webpage detection-Reference-Cited by-同舟云学术

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A stacking model using URL and HTML features for phishing webpage detection

Published:2019-05 Issue: Volume:94 Page:27-39
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Li Yukun^ORCID,Yang Zhenguo,Chen Xu^ORCID,Yuan Huaping^ORCID,Liu Wenyin

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Guangdong Innovative Research Team Program

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference54 articles.

1. APWG, Phishing activity trends report, http://docs.apwg.org/reports/apwg_trends_report_q4_2016.pdf, accessed Dec 10, 2017.

2. G. Developers, Safe browsing api-developer guide v3, https://developers.google.com/safebrowsing/developers_guide_v3, accessed May 13, 2014.

3. Towards a contingency approach with whitelist- and blacklist-based anti-phishing applications: What do usability tests indicate?;Li;Behav. Inf. Technol.,2014

4. Phishing detection via identification of website identity;Chang,2013

5. GoldPhish: Using images for content-based phishing analysis;Dunlop,2010

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