Efficient deep learning techniques for the detection of phishing websites-Reference-Cited by-同舟云学术

Efficient deep learning techniques for the detection of phishing websites

Published:2020-06-27 Issue:1 Volume:45 Page:
ISSN:0256-2499
Container-title:Sādhanā
language:en
Short-container-title:Sādhanā

Author:

Somesha M,Pais Alwyn Roshan,Rao Routhu Srinivasa,Rathour Vikram Singh

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

https://link.springer.com/content/pdf/10.1007/s12046-020-01392-4.pdf

Reference49 articles.

1. Rao R S and Pais A R 2019 Detection of phishing websites using an efficient feature-based machine learning framework. Neural Comput. Appl. 31: 3851–3873

2. APWG 2018 Phishing attack trends reports, first quarter 2018. https://docs.apwg.org//reports/apwg_trends_report_q1_2018.pdf, published July 31, 2018

3. Fu A Y, Wenyin L and Deng X 2006 Detecting phishing web pages with visual similarity assessment based on earth mover’s distance (emd). IEEE Trans. Dependable Secure Comput. 3: 301–311

4. Wenyin L, Huang G, Xiaoyue L, Min Z and Deng X 2005 Detection of phishing webpages based on visual similarity. In: Special Interest Tracks and Posters of the 14th International Conference on World Wide Web, ACM, pp. 1060–1061

5. Hara M, Yamada A and Miyake Y 2009 Visual similarity-based phishing detection without victim site information. In: Proceedings of the IEEE Symposium on Computational Intelligence in Cyber Security, CICS’09, IEEE, pp. 30–36

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