As artificial intelligence (AI) systems become increasingly critical to national security and other high-stakes domains, the risk of model theft, manipulation, and misuse by sophisticated adversaries grows. In this report, the authors present a vertically integrated security strategy for secure inference data centers (SIDCs): purpose-built, Security Level 5 facilities designed to protect trained AI models against the most-advanced nation-state adversaries.
The authors’ proposed SIDC architecture employs rigorous system partitioning, unidirectional data diodes, and formally verified cross-realm protocols to ensure the confidentiality and integrity of model weights, algorithms, and inference data.
The report details a concept-to-circuit methodology, emphasizing minimal, purpose-built features and the use of formal methods for high-assurance components. While operational constraints—such as limited connectivity, fixed software, and restricted physical access—limit general applicability, SIDCs are recommended for national security, emergency response, and pilot deployments.
SIDCs can be implemented today using proven technologies. The authors recommend that stakeholders initiate detailed design and prototyping to accelerate deployment.
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