Article Series: Securing the AI Stack: From Model to Production
Your AI deployment is one misconfiguration away from breach. Here's the layered defense framework enterprises are adopting now.
Why it matters
As AI moves from research to production, security governance and MLOps resilience have become board-level concerns. This series addresses the infrastructure and policy gaps that separate prototype from production-ready systems.
The key facts
9 to knowFocus on layered defense architecture for AI systems
MLOps and governance integration as production requirements
Shift from vulnerable prototypes to resilient deployments
Security frameworks for end-to-end AI stack protection
Focus on layered defense across AI stack
MLOps and governance as core security pillars
Addresses transition from prototype to production resilience
Author: Claudio Masolo
Published on InfoQ (enterprise architecture audience)
Go to the source
InfoQ AI/MLinfoq.com
Publisher excerpt: This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance. By Claudio Masolo