URL Based Detection of Phishing Using Random Forest Algorithm and SVM

  • Usha Kiruthika, Kowshik Varma, Sunvith Bangarraju

Abstract

Malicious sites generally advance the development of Internet crimes and oblige the improvement of web services. As a result, there has been a strong inspiration to make basic responses to keep the customer from visiting such destinations by making the customer aware of the threat the site presents. We propose a learning based approach to manage request destinations into 3 classes: Benign, Malware and Malicious. Our mechanism just separates the Uniform Resource Locator itself without accessing the contents of the site pages. Thus, it kills the run-time latency and the possibility of introducing customers to the browser based vulnerabilities. This paper proposes a feasible course for the area of phishing destinations using Random Forest Algorithm, SVM and few specific URL features for better results.

Published
2020-05-15
How to Cite
Usha Kiruthika, Kowshik Varma, Sunvith Bangarraju. (2020). URL Based Detection of Phishing Using Random Forest Algorithm and SVM. International Journal of Advanced Science and Technology, 29(9s), 3177 - 3183. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/15875