In this episode of the Redefining Cybersecurity podcast, Sean Martin is joined by Mick Douglas and Dinis Cruz to delve into a debatable topic: The role and effectiveness of Language Model (LLM) AI in Security Incident and Event Management (SIEM) systems.

Mick, with a rich history in cybersecurity, contends that while AI has its place, he doesn't believe it belongs in the SIEM itself. In contrast, Dinis cites the potential of AI to make SIEMs more productive by cleaning up data, reducing noise, and improving signal value. They discuss the issues of handling vast data sets, the potential for AI to help identify and manage anomalies, and how to create learning environments within SIEM. However, concerns were also raised regarding false positives, trust issues with AI and the significant computational costs to implement and maintain these AI systems.

Key Questions Explored:

Does AI belong in SIEM systems?
What potential does AI bring to SIEM?
What are the potential issues with implementing and maintaining AI in SIEM?

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Resources

Inspiring LinkedIn Post: https://www.linkedin.com/posts/mick-douglas_first-let-me-be-really-clear-for-the-near-activity-7146143942739124224-a4vl/

Inspiring Twitter Post: https://twitter.com/bettersafetynet/status/1740370001973154010

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