S., Muthuselvan and R., Karthikeyan and M., Rajasekaran and K., Rajakumari and S., Rajes kannan and S., Anupriya (2024) Machine Learning for the Detection of Uniform Resource Locator Phishing. Springer. pp. 40-48. ISSN 2327-3453
Full text not available from this repository.Abstract
In recent times, phishing attempts have grown in frequency as fraudsters employ diverse tactics to deceive gullible victims into divulging confidential information, like financial details or login credentials. One of the most common methods of phishing is through the use of URLs, where attackers create fake web pages that mimic legitimate sites and use them to steal information from users to combat this threat, researchers and security experts have turned to machine learning techniques to develop algorithms that can accurately detect phishing URLs. In this paper, review the current state of the art in URL phishing detection using machine learning, including the various approaches and algorithms that have been developed. © 2024 Elsevier B.V., All rights reserved.
| Item Type: | Article |
|---|---|
| Subjects: | Computer Science > Computer Science Applications |
| Divisions: | Engineering and Technology > Aarupadai Veedu Institute of Technology, Chennai |
| Depositing User: | Unnamed user with email techsupport@mosys.org |
| Last Modified: | 27 Nov 2025 05:51 |
| URI: | https://vmuir.mosys.org/id/eprint/1516 |
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