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Practical Foundations for Securing AI

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Manage episode 418235989 series 3461851
Contenu fourni par MLSecOps.com. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par MLSecOps.com ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

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In this episode of the MLSecOps Podcast, we delve into the critical world of security for AI and machine learning with our guest Ron F. Del Rosario, Chief Security Architect and AI/ML Security Lead at SAP ISBN. The discussion highlights the contextual knowledge gap between ML practitioners and cybersecurity professionals, emphasizing the importance of cross-collaboration and foundational security practices. We explore the contrasts of security for AI to that for traditional software, along with the risk profiles of first-party vs. third-party ML models. Ron sheds light on the significance of understanding your AI system's provenance, having necessary controls, and audit trails for robust security. He also discusses the "Secure AI/ML Development Framework" initiative that he launched internally within his organization, featuring a lean security checklist to streamline processes. We hope you enjoy this thoughtful conversation!

Thanks for checking out the MLSecOps Podcast! Get involved with the MLSecOps Community and find more resources at https://community.mlsecops.com.
Additional tools and resources to check out:
Protect AI Guardian: Zero Trust for ML Models

Protect AI’s ML Security-Focused Open Source Tools

LLM Guard Open Source Security Toolkit for LLM Interactions

Huntr - The World's First AI/Machine Learning Bug Bounty Platform

  continue reading

40 episodes

Artwork
iconPartager
 
Manage episode 418235989 series 3461851
Contenu fourni par MLSecOps.com. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par MLSecOps.com ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Send us a text

In this episode of the MLSecOps Podcast, we delve into the critical world of security for AI and machine learning with our guest Ron F. Del Rosario, Chief Security Architect and AI/ML Security Lead at SAP ISBN. The discussion highlights the contextual knowledge gap between ML practitioners and cybersecurity professionals, emphasizing the importance of cross-collaboration and foundational security practices. We explore the contrasts of security for AI to that for traditional software, along with the risk profiles of first-party vs. third-party ML models. Ron sheds light on the significance of understanding your AI system's provenance, having necessary controls, and audit trails for robust security. He also discusses the "Secure AI/ML Development Framework" initiative that he launched internally within his organization, featuring a lean security checklist to streamline processes. We hope you enjoy this thoughtful conversation!

Thanks for checking out the MLSecOps Podcast! Get involved with the MLSecOps Community and find more resources at https://community.mlsecops.com.
Additional tools and resources to check out:
Protect AI Guardian: Zero Trust for ML Models

Protect AI’s ML Security-Focused Open Source Tools

LLM Guard Open Source Security Toolkit for LLM Interactions

Huntr - The World's First AI/Machine Learning Bug Bounty Platform

  continue reading

40 episodes

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