Leveraging Big Data Analytics for Enhanced Cybersecurity: A Comprehensive Analysis of Threat Detection, Incident Response, and SIEM Systems

Ankur Partap Kotwal

doi:10.32628/CSEIT2410612414

Authors

Ankur Partap Kotwal Meta, USA Author

DOI:

https://doi.org/10.32628/CSEIT2410612414

Keywords:

Big Data Analytics, Cybersecurity, Threat Detection, SIEM Systems, Incident Response

Abstract

This article comprehensively analyzes big data analytics applications in cybersecurity, focusing on threat detection, incident response, and Security Information and Event Management (SIEM) systems. The article explores how organizations leverage big data analytics to enhance their cybersecurity posture through advanced threat detection mechanisms, improved incident response capabilities, and sophisticated SIEM implementations. The article examines various aspects of modern cybersecurity systems, including anomaly detection, predictive analytics, real-time monitoring architectures, and root cause analysis frameworks. Through detailed case studies of major platforms, including Google Security Analytics, IBM QRadar, and Splunk, the article provides insights into practical implementations and their impact on organizational security. The article also addresses emerging technologies such as quantum computing and their implications for future cybersecurity frameworks. By analyzing implementation guidelines, best practices, and research opportunities, this article offers valuable insights for organizations seeking to enhance their cybersecurity capabilities through big data analytics while providing a framework for future developments in this rapidly evolving field.

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References

Hamed Okhravi, "A Cybersecurity Moonshot," IEEE Security & Privacy, May-June 2021. https://ieeexplore.ieee.org/document/9374753 DOI: https://doi.org/10.1109/MSEC.2021.3059438

M. Mazhar Rathore et al., "The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities," IEEE Access, February 2021. https://ieeexplore.ieee.org/document/9359733 DOI: https://doi.org/10.1109/ACCESS.2021.3060863

Yassine Maleh et al., "Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence," IEEE Transactions on Big Data, 2019. https://ieeexplore.ieee.org/document/9950373

Shilpa Mahajan, "Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection," Wiley eBooks, 2024. https://onlinelibrary.wiley.com/doi/book/10.1002/9781394196470?msockid=228aad31782d6ce406e9b9de79c56d17

Ayesha Naseer et al., "The Effect of Big Data Analytics in Enhancing Agility in Cybersecurity Incident Response," 2022 IEEE 16th International Conference on Open Source Systems and Technologies (ICOSST). https://ieeexplore.ieee.org/abstract/document/10016853 DOI: https://doi.org/10.1109/ICOSST57195.2022.10016853

Steve Anson, "Applied Incident Response," Wiley eBooks, 2020. https://onlinelibrary.wiley.com/doi/book/10.1002/9781119560302?msockid=228aad31782d6ce406e9b9de79c56d17

Timothy I Alatise and Olusegun E Nottidge, "Threat Detection and Response with SIEM System," https://www.computersciencejournals.com/ijcit/article/78/5-1-9-355.pdf DOI: https://doi.org/10.33545/2707661X.2024.v5.i1a.78

Kothekar, A. M., Patil, S., & Packt Publishing. "Building a Next-Gen SOC with IBM QRadar: Accelerate your security operations and detect cyber threats effectively," 2023. https://ieeexplore.ieee.org/book/10251303

The Quantum Insider, "Quantum Computing Revolution: The Future of Technology," IEEE Transactions on Quantum Engineering, 2023. https://www.sciastra.com/blog/quantum-computing-revolution-the-future-of-technology/