Phishing Website Detection Using ML

Authors

  • Nikhil K  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India
  • Dr. Rajesh D S  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India
  • Dhanush Raghavan  Department of Computer Science, Srinivas Institute of Technology, Mangalore, Karnataka, India

DOI:

https://doi.org/10.32628/CSEIT217354

Keywords:

Phishing Detection, Decision Tree, Machine-learning

Abstract

Phishing is one kind of cyber-attack , it is a most dangerous and common attack to retrieve personal information, account details, credit card credentials, organizational details or password of a client to conduct transactions. Phishing websites seem to like the relevant ones and it is difficult to differentiate among those websites. It is one of the most threatening that every individuals and organization faced. URLs are known as web sites are by which users locate information on the internet. The review creates warning of phishing attacks, detection of phishing attacks and motivate the practice of phishing prevention among the readers. With the huge number of phishing emails or messages received now days, companies or individuals are not able to find all of them.

References

  1. www.researchgate.net/publication/328541785_Phishing_Website_Detection_using_Machine_Learning_Algorithms
  2. Mohammad R., Thabtah F. McCluskey L., (2015) Phishing websites dataset. Available: https://archive.ics.uci.edu/ml/datasets/Phishing+Websites Accessed January 2016
  3. Mahmoud Khonji, Youssef Iraqi, "Phishing Detection: A Literature Survey IEEE, and Andrew Jones, 2013
  4. Rishikesh Mahajan (2018) “Phishing Website Detection using Machine Learning Algorithms”
  5. Purvi Pujara, M. B.Chaudhari (2018) “Phishing Website Detection using Machine Learning : A Review”
  6. S. Abu-Nimeh and T. M. Chen. Proliferation and detection of blog spam. Security & Privacy, IEEE, 8(5):42–47, 2010.
  7. Jalil Nourmohammadi Khiarak (2017) “What is Machine Learning”
  8. Tenzin Dakpa, Peter Augustine (2017) “Study of Phishing Attacks and Preventions”
  9. Sadia Afroz, Rachel Greenstadt (2017) “PhishZoo: Detecting Phishing Websites By Looking at Them”
  10. Srushti Patil, and Sudhir Dhage, “A Methodical Overview On Phishing Detection Along With An Organized Way To Construct an Anti-Phishing Framework”, 2019 5th International Conference On Advanced Computing & Communication System(ICACCS), pp. 1-6

Downloads

Published

2021-08-30

Issue

Section

Research Articles

How to Cite

[1]
Nikhil K, Dr. Rajesh D S, Dhanush Raghavan, " Phishing Website Detection Using ML" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 4, pp.194-198, July-August-2021. Available at doi : https://doi.org/10.32628/CSEIT217354