This paper is published in Volume-8, Issue-3, 2022
Area
Computer Science and Engineering
Author
Koushik Kumar Reddy, E. Surendra, M. Sai Nikhil Gowd, N. Jaya Pradeep Reddy, Narasimhayya B. E.
Org/Univ
Jain University, Kanakapura, Bengaluru, India
Pub. Date
17 June, 2022
Paper ID
V8I3-1404
Publisher
Keywords
Machine Learning, Logistic Regression, Random Forest, Naive Bayes, K neighbor, F1 score, and Accuracy.

Citationsacebook

IEEE
Koushik Kumar Reddy, E. Surendra, M. Sai Nikhil Gowd, N. Jaya Pradeep Reddy, Narasimhayya B. E.. Detection of phishing websites using a Machine Learning approach, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Koushik Kumar Reddy, E. Surendra, M. Sai Nikhil Gowd, N. Jaya Pradeep Reddy, Narasimhayya B. E. (2022). Detection of phishing websites using a Machine Learning approach. International Journal of Advance Research, Ideas and Innovations in Technology, 8(3) www.IJARIIT.com.

MLA
Koushik Kumar Reddy, E. Surendra, M. Sai Nikhil Gowd, N. Jaya Pradeep Reddy, Narasimhayya B. E.. "Detection of phishing websites using a Machine Learning approach." International Journal of Advance Research, Ideas and Innovations in Technology 8.3 (2022). www.IJARIIT.com.

Abstract

In recent years, advancements in Internet and cloud technologies have led to a significant increase in electronic trading in which consumers make online purchases and transactions. This growth leads to unauthorized access to users’ sensitive information and damages the resources of an enterprise. Phishing is one of the familiar attacks that trick users to access malicious content and gain their information. In terms of website interface and uniform resource locator (URL), most phishing webpages look identical to the actual webpages. Various strategies for detecting phishing websites, such as blacklist, heuristic, Etc., have been suggested. However, due to inefficient security technologies, there is an exponential increase in the number of victims. The anonymous and uncontrollable framework of the Internet is more vulnerable to phishing attacks. Existing research works show that the performance of the phishing detection system is limited. There is a demand for an intelligent technique to protect users from the cyber-attacks