AI-Powered Log Analysis for Proactive Threat Detection in Enterprise Networks

Authors

  • Kathiravan Thangavelu Microsoft Corp, USA Author
  • Arun Ayilliath Keezhadath Amazon Web Services, USA Author
  • Amsa Selvaraj Amtech Analytics, USA Author

Keywords:

AI-powered log analysis, proactive threat detection, machine learning, anomaly detection

Abstract

AI powered log analysis has turn out to be a crucial component of modern security framework which enables proactive threat detection in enterprise network. The increasing amount of refined cyber threats makes it compulsory to use advanced analytical techniques that goes beyond traditional rule-based security system. This research paper investigates the implementation of machine learning based log analytics for a anomaly detection which focuses on platforms such as ELK (Elasticsearch, Logstash, Kibana) and NewRelic.

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Published

27-03-2022

How to Cite

[1]
Kathiravan Thangavelu, Arun Ayilliath Keezhadath, and Amsa Selvaraj, “AI-Powered Log Analysis for Proactive Threat Detection in Enterprise Networks ”, Essex Journal of AI Ethics and Responsible Innovation, vol. 2, pp. 33–66, Mar. 2022, Accessed: Apr. 16, 2025. [Online]. Available: https://ejaeai.org/index.php/publication/article/view/14