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DOI Prefix: 10.47001/IRJIET
Vol 8 No 1 (2024): Volume 8, Issue 1, January 2024 | Pages: 74-80
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 26-01-2024
Machine learning has emerged as a climatic technology in contemporary and prospective cyber threat intel systems, with numerous jurisdictions seamlessly integrating it into their operations. However, the current state of machine learning in cyber defence is still in its early stages, foreshadowing a noticeable unexplored research territory and practical implementation. This paper marks the initial endeavour to offer a comprehensive understanding of machine learning within the entire spectrum of cybersecurity jurisdictions, catering to potential end users with enthusiasm in this field of study. This paper aims to serve as a source of inspiration for significant advancements in ML within the cyber defence zone, laying the groundwork for the broader adoption of ML mitigations to safeguard present and heuristic systems.
Machine Learning, Cybersecurity, Enthusiasm technology, Jurisdictions, Supervised, Un-Supervised, Domain, Elucidating, Cyber Vulnerabilities, Phishing Attacks, Intrusion Detection Systems, SNORT, Host Intrusion Detection Systems
Bishwajit Das, Nikita Yadav, Deepa Chauhan, Sanju Gupta, “CyMac: Diving Deep into the Application of Machine Learning Algorithms in Cyber Security” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 8, Issue 1, pp 74-80, January 2024. Article DOI https://doi.org/10.47001/IRJIET/2024.801010
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