Phishing Website Detection Based on URL

Authors

  • Salvi Siddhi Ravindra  Computer Engineering Department, Shah & Anchor Kutchhi Engineering College Mumbai, Maharashtra, India
  • Shah Juhi Sanjay  Computer Engineering Department, Shah & Anchor Kutchhi Engineering College Mumbai, Maharashtra, India
  • Shaikh Nausheenbanu Ahmed Gulzar  Computer Engineering Department, Shah & Anchor Kutchhi Engineering College Mumbai, Maharashtra, India
  • Khodke Pallavi  Computer Engineering Department, Shah & Anchor Kutchhi Engineering College Mumbai, Maharashtra, India

DOI:

https://doi.org//10.32628/CSEIT2173124

Keywords:

URLs, Phishing, Legitimate, Machine Learning.

Abstract

In today's era, due to the surge in the usage of the internet and other online platforms, security has been major attention. Many cyberattacks take place each day out of which website phishing is the most common issue. It is an act of imitating a legitimate website and thereby tricking the users and stealing their sensitive information. So, concerning this problem, this paper will introduce a possible solution to avoid such attacks by checking whether the provided URLs are phishing URLs or legitimate URLs. It is a Machine Learning based system especially Supervised learning where we have provided 2000 phishing and 2000 legitimate URL dataset. We have taken into consideration the Random Forest Algorithm due to its performance and accuracy. It considers 9 features and hence detects whether the URL is safe to access or a phishing URL.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-06-30

Issue

Volume 7, Issue 3, May-June-2021

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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

How to Cite

[1]
Salvi Siddhi Ravindra, Shah Juhi Sanjay, Shaikh Nausheenbanu Ahmed Gulzar, Khodke Pallavi, " Phishing Website Detection Based on URL, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 3, pp.589-594, May-June-2021. Available at doi : https://doi.org/10.32628/CSEIT2173124