Executive Summary
Global data center demand is predicted to triple by 2030, with nearly 70 percent of the demand being driven by artificial intelligence (AI) workloads. The surge in AI data center demand is fueled by the exponentially increasing use of AI at work and integration into daily lives as well as the recognition that the technology can influence geopolitics, reorder the global economy, drive scientific discovery, and transform human lives and society.
Two barriers to supporting this increased demand for AI data centers are the required energy and security. While the energy concern has been highlighted and publicized, the security gaps have been understated: AI data centers have mostly been considered as a part of traditional data centers and critical infrastructure, with no separate or focused effort for AI data center cybersecurity requirements.
However, AI data centers face an expanded set of threats. A successful cyberattack on an AI data center could enable threat actors to extract information about the AI model and weights, risking loss of sensitive training data as well as the integrity and confidentiality of the AI model. When AI models are exfiltrated, hackers can create vulnerabilities in AI models and bias outputs, as well as more easily and cheaply replicate AI models.
Thus, this report recommends a comprehensive framework for AI data center security that spans six layers of security and three types of approaches. The six layers of security are (1) hardware & compute, (2) network & storage, (3) model & data, (4) software & application, (5) physical access, and (6) geopolitical. Given the complexity, these six layers also require three approaches: technical, corporate policy, and national governance. Under this framework, the report’s recommendations are as follows:
- Bridge the gaps between the technical, corporate policy, and national governance approaches with a framework that maps the threats to AI data centers across the six layers of security.
- Implement existing research and standards for technical requirements in an AI data center.
- Require technical measures across the six layers of security in corporate policies.
- Focus national governance measures on incentivizing operators to meet the technical and corporate policies needed for a cyber-secure AI data center.