Cybersecurity Threat Detection using Machine Learning on Network Traffic
Web phishing is a prevalent online attack in which victims are tricked into revealing their personal information by visiting fraudulent websites. Phishers often use URL shortening tools to disguise malicious links, making it easier to steal sensitive data such as usernames, passwords, and banking details. These phishing websites are designed to mimic legitimate ones, making detection more challenging. As phishing techniques continue to evolve rapidly alongside technological advancements, the need for effective anti-phishing systems has become increasingly crucial. Machine learning has emerged as a powerful tool for recognizing and mitigating phishing scams. This article provides a comprehensive overview of machine learning techniques for phishing detection and their effectiveness in combating online threats.
Authors
- S. Jeya Lakshmi (ORCID: https://orcid.org/0009-0002-8962-6992)
- R. Saravanakumar (ORCID: https://orcid.org/0000-0002-4772-1732)
- N. Nithya (ORCID: https://orcid.org/0000-0001-9933-8711)
- A. Akila
- M. Vargheese (ORCID: https://orcid.org/0009-0003-3372-4451)
- R. Rithi
Institutions
- Karpagam Academy of Higher Education (IN)
Publication Details
- Published
- 2025-03-19
- DOI
- https://doi.org/10.1109/iciccs65191.2025.10985032
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00