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AI-driven cybersecurity: Utilizing machine learning and deep learning techniques for real-time threat detection, analysis, and mitigation in complex IT networks
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Abstract
With the escalating complexity of IT networks and the surge in cyber threats, the need for advanced, real-time security solutions has never been more paramount. Machine learning (ML) and deep learning (DL) present promising avenues for enhancing the detection, analysis, and mitigation of threats in these intricate networks. The paper delves into the confluence of ML and DL techniques in the realm of cybersecurity, focusing on their application for real-time threat detection within IT infrastructures. Drawing from recent research and developments, the study underscores the potential of these techniques in outmaneuvering conventional security models, while also shedding light on the inherent challenges and areas for future exploration.
Keywords
machine learning, deep learning, real-time threat detection, IT network security, cybersecurity
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Cite this article
Alionsi,D.D.D. (2023). AI-driven cybersecurity: Utilizing machine learning and deep learning techniques for real-time threat detection, analysis, and mitigation in complex IT networks. Advances in Engineering Innovation,3,27-31.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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