Comparative analysis of ML Algorithms for effective phishing URL detection
Authors
De Silva, Weligodage Suharshi Lakshika
Issue Date
2024
Degree
Master of Science (MSc) in Business Analytics
Publisher
Dublin Business School
Rights holder
Rights
Abstract
Cybersecurity, an increasingly critical field, is under constant threat from evolving cyberattacks. Phishing websites, a prominent method for attackers to deceive users and steal sensitive information, require effective detection systems. This study, focusing on developing a highly accurate ML model to predict the phishing nature of websites, is a significant contribution to the field. The study highlights the importance of balancing accuracy with real-time applicability, emphasising the need for quick response times in practical phishing detection systems. Future improvements may include integrating incremental learning and hybrid models to enhance detection capabilities further.