Prediction of Phishing Websites Using Machine Learning

Authors

  • S. Bargunan Assistant Professor, Department of Computer Science and Engineering, Agni College of Technology, Chennai, India
  • R. Revathi Under Graduate, Department of Computer Science and Engineering, Agni College of Technology, Chennai, India
  • A. Priyadharshini Under Graduate, Department of Computer Science and Engineering, Agni College of Technology, Chennai, India

Keywords:

anti-phishing, machine learning, random forest, prediction

Abstract

A large number of people buy things online and pay for them using different websites. Several websites ask users for personal information such as usernames, passwords, and credit card numbers, among other things, for harmful purposes. Phishing websites are exactly what they sound like. We suggested an intelligent, versatile, and effective solution based on machine learning techniques for detecting and predicting phishing websites. To extract the phishing data sets criteria and identify their authenticity, we used a classification algorithm and approaches. In the final phishing detection rate, URL and Domain Identity, as well as security and encryption criteria, can be used to detect the phishing website. Our system will utilize a machine learning algorithm to determine whether or not the website is phishing. Many E-commerce businesses can utilize this programme to make the entire transaction process secure. In comparison to other classic classification algorithms, the machine learning algorithm utilized in this system performs better. This technique also allows users to purchase things online without fear of being scammed.

Downloads

Download data is not yet available.

Downloads

Published

20-06-2022

How to Cite

[1]
S. Bargunan, R. Revathi, and A. Priyadharshini, “Prediction of Phishing Websites Using Machine Learning”, IJRESM, vol. 5, no. 6, pp. 169–172, Jun. 2022.

Issue

Section

Articles