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"Securing The AI Data Center & AI Factory"

AI factories and data centers face threats like prompt injection, model poisoning, and data leakage. A defense-in-depth strategy across applications, infrastructure, and governance can secure AI environments without reducing performance. Read this white paper for a framework on AI data center security.

As enterprises deploy private AI infrastructure and large language models, a new attack surface emerges. AI factories and data centers face risks like prompt injection, model poisoning, data leakage, and supply chain compromise that traditional security cannot address.

This white paper provides a framework for securing securing private LLMs and AI infrastructure end-to-end, from network perimeter and prompts, to GPU clusters, Kubernetes workloads and governance. Key topics include:

• Layered, defense-in-depth security for AI applications and infrastructure
• Hardware-level security to preserve GPU performance
• Governance for compliance, supply chain risk, and AI frameworks

Read the white paper for a comprehensive approach to AI security.

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