Phishing Website Detection Based on Machine Learning Algorithm

Authors

  • 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

DOI:

https://doi.org/10.32628/IJSRST523103124

Keywords:

Phishing Website Detection, Machine Learning, Webpage Similarity Comparation

Abstract

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.

References

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International Journal of Scientific Research in Science and Technology

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Published

2023-06-30

Issue

Volume 10, Issue 3, May-June-2023

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
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), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 10, Issue 3, pp.562-570, May-June-2023. Available at doi : https://doi.org/10.32628/IJSRST523103124