Protecting and Mitigating Against Cyber Threats

9Detection and Proactive Prevention of Website Swindling Using Hybrid Machine Learning Model

G. Nithish Rao^*, J.M.S. Abhinav and M. Venkata Krishna Reddy

Department of Computer Science and Engineering, Chaitanya Bharathi Institute of Technology (A), Gandipet, Hyderabad, India

Abstract

Phishing is a form of criminal fraud in the realm of computer security in which an online scammer poses as a legitimate business or organization in an email in an effort to trick unsuspecting victims into giving over sensitive information (such as login credentials, passwords, or credit card numbers) for malicious use. By extracting and analyzing numerous aspects of genuine and phishing URLs, this paper proposes a method that works with machine learning technology for phishing URL identification. Decision Tree, Random Forest, and Support Vector Machine are three of many Machine Learning algorithms that can identify phishing attempts on websites. Research and analysis have led us to the conclusion that no one security measure can entirely eradicate phishing attacks. Nevertheless, we believe that by combining effective learning models with the correct implementation of existing security measures, we can significantly lessen the frequency of phishing attacks and the damage they cause. The search for reliable and consistent detection methods for phishing websites has begun among cyber security experts. Using hybrid models can improve consumers’ ability to recognize and prevent frauds due to their ...