Manuscript Number : IJSRST523103124

Phishing Website Detection Based on Machine Learning Algorithm

Authors(4) :-Prof. A. V. Mote, Hitesh Y. Patil, Prachi R. Patil, Omkar S. Ombase

Phishing websites utilise a variety of techniques to imitate the URL address and page content of a legitimate website in order to steal users' personal information. In this study, we analyse the structural properties of the phishing website URL, extract 12 different types of data, and train four machine learning algorithms. Then, in order to identify unknown URLs, utilise the method that performed the best as our model. The recommendation of the original regular web page of the phishing web page is implemented after a snapshot of the web page is extracted and compared with the regular web page snapshot.

Authors and Affiliations

Prof. A. V. Mote
Department of Computer Engineering, Zeal College of Engineering and Research Pune, Maharashtra, India
Hitesh Y. Patil
Department of Computer Engineering, Zeal College of Engineering and Research Pune, Maharashtra, India
Prachi R. Patil
Department of Computer Engineering, Zeal College of Engineering and Research Pune, Maharashtra, India
Omkar S. Ombase
Department of Computer Engineering, Zeal College of Engineering and Research Pune, Maharashtra, India

Phishing Website Detection, Machine Learning, Webpage Similarity Comparation

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Publication Details

Published in : Volume 10 | Issue 3 | May-June 2023
Date of Publication : 2023-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 562-570
Manuscript Number : IJSRST523103124
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Prof. A. V. Mote, Hitesh Y. Patil, Prachi R. Patil, Omkar S. Ombase, " Phishing Website Detection Based on Machine Learning Algorithm", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 10, Issue 3, pp.562-570, May-June-2023. Available at doi : https://doi.org/10.32628/IJSRST523103124    
Journal URL : https://ijsrst.com/IJSRST523103124
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