The Future of SIEM in a Machine Learning-Driven Cybersecurity Landscape

Main Article Content

Srinivas Reddy Pulyala

Abstract

As cyber threats become increasingly sophisticatedand complex, traditional Security Information and Event Management (SIEM) systems are struggling to keep up. The integration of artificial intelligence (AI) and machine learning (ML) into SIEM tools is transforming the way organizations detect, investigate, and respond to security incidents. This paper explores the future of SIEM tools in the context of the evolving cybersecurity landscape and discusses how organizations can prepare for the adoption of ML-enabled SIEM systems.ML-enabled SIEM systems significantly enhance the capabilities of traditional SIEM tools,enabling them to more effectively detect and respond to both known andemergingthreats.Organizations must develop a robust data strategy,invest in talent,and adopt ML-enabled SIEM solutions gradually to fully take advantage ofthepotentialof these technologies.Staying up-to-date with the latest trends in ML and cybersecurity isalsocrucial for organizations to maximize the benefits of ML-enabled SIEM tools.

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How to Cite
Pulyala, S. R. . (2023). The Future of SIEM in a Machine Learning-Driven Cybersecurity Landscape. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 14(03), 1309–1314. https://doi.org/10.61841/turcomat.v14i03.14392
Section
Research Articles

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