How to implement zero trust for AI

As organizations embed AI into business systems, they also expand the attack surface. Applying zero trust to AI can help mitigate the risk.

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• Damon Garn, Cogspinner Coaction

AI environments involve complex data pipelines, model-training infrastructure, APIs and third-party components, all of which introduce new security risks.

Modern security techniques-- with and without AI -- recognize that traditional trusted-network approaches are inadequate. AI systems ingest new data, interact with users and integrate with other platforms, creating multiple entry points for attackers. A zero-trust model with continuous verification, strict access controls and ongoing monitoring offers a practical framework for protecting AI systems without slowing innovation.

Read on to learn how to apply zero-trust principles to AI by securing data, models, workflows and people.