Hybrid AI Models for Phishing URL Detection: A Unified Approach to  Mitigating Cyber Threats

M Dattatreya Goud,   Dr.P.Venkateswarlu,

Hybrid AI Models for Phishing URL Detection: A Unified Approach to Mitigating Cyber Threats

Authors

M Dattatreya Goud, Dr.P.Venkateswarlu,

Keywords:

Phishing, Cybersecurity, Machine Learning, Deep Learning, URL Filtering, Phishing Detection Website Analysis, Phishing Strategies

Abstract

Phishing remains among the top threats in the cybersecurity domain, in which the attackers
induce people to provide sensitive

References

. Divakaran, Dinil Mon, and Adam Oest. "Phishing Detection

Leveraging Machine Learning and Deep Learning: A Review." arXiv preprint arXiv:2205.07411 (2022).

. Das Guptta, S., Shahriar, K.T., Alqahtani, H., Alsalman, D. and Sarker, I.H., 2022. Modeling Hybrid Feature-Based Phishing Websites Detection Using Machine Learning Techniques. Annals of Data Science, pp.1-26.

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Published

2024-09-25

How to Cite

M Dattatreya Goud, Dr.P.Venkateswarlu,. (2024). Hybrid AI Models for Phishing URL Detection: A Unified Approach to Mitigating Cyber Threats . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 4923–4928. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3026