Application and Analysis of Phishing Website Detection in Machine Learning and Neural Networks

Author:

Pooja A. S. S. V. Lakshmi,Sridhar M.,Ramesh G.

Publisher

Springer Singapore

Reference17 articles.

1. Shukla, Z., Zala, K., Kotak, R.: A survey of website phishing detection techniques. Int. J. Fut. Revol. Comput. Sci. Commun. Eng. 4(1). http://www.ijfrcsce.org

2. Pujara, P., Chaudhari, M.B.: Phishing website detection using machine learning: a review. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol. 3(7), 2456–3307 (2018)

3. https://docs.apwg.org/reports/apwg_trends_report_q3_2019.pdf

4. Patil1, D.R., Patil, J.P.: Feature-based Malicious URL and attack type detection using multi-class classification. ISeCure ISC Int. J. Inf. Secur. 10(2), 141–162. http://www.isecure-journal.org

5. https://randed.com/types ofphishing/?lang=en

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