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The Everything Feed - All Packet Pushers Pods

PP033: AI and Machine Learning 101 for Cybersecurity

Oct 1, 2024
Jeff Crume, a distinguished engineer and cybersecurity architect at IBM, dives into the world of AI and machine learning in cybersecurity. He clarifies misconceptions and explains how these technologies can detect anomalies and strengthen security. The conversation covers the challenges of siloed data and the potential of generative AI for innovative threat assessments. Crume also emphasizes the importance of transparency in AI models and the need for adaptive strategies to tackle evolving threats, all while mixing in humor and personal anecdotes.
46:21

Episode guests

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Quick takeaways

  • Understanding the distinction between AI and machine learning is crucial for evaluating cybersecurity vendor claims and product capabilities.
  • Machine learning enhances cybersecurity by identifying patterns and anomalies in data, improving detection of unauthorized activities more efficiently than traditional methods.

Deep dives

Understanding AI and Machine Learning Definitions

Artificial Intelligence (AI) aims to replicate or surpass human intelligence, which often confuses its definitions within cybersecurity. Among its subfields, machine learning (ML) is notable for its ability to learn from data patterns rather than being explicitly programmed. This distinction is crucial in cybersecurity, as it allows systems to find anomalies by feeding them large datasets and observing deviations from established norms, such as unusual login activities or data modifications. By clarifying these definitions and distinguishing between AI and ML, professionals can more effectively evaluate the capabilities of various cybersecurity vendors.

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