Toward Trustworthy AI: A Zero-Trust Framework for Foundational Models
As foundational AI models grow in power and reach, they also expose new attack surfaces, vulnerabilities, and ethical risks. This white paper by the Secure Systems Research Center (SSRC) at the Technology Innovation Institute (TII) outlines a comprehensive framework to ensure security, resilience, and safety in large-scale AI models. By applying Zero-Trust principles, the framework addresses threats across training, deployment, inference, and post-deployment monitoring. It also considers geopolitical risks, model misuse, and data poisoning, offering strategies such as secure compute environments, verifiable datasets, continuous validation, and runtime assurance. The paper proposes a roadmap for governments, enterprises, and developers to collaboratively build trustworthy AI systems for critical applications.
Download this free whitepaper now!
As foundational AI models grow in power and reach, they also expose new attack surfaces, vulnerabilities, and ethical risks. This white paper by the Secure Systems Research Center (SSRC) at the Technology Innovation Institute (TII) outlines a comprehensive framework to ensure security, resilience, and safety in large-scale AI models. By applying Zero-Trust principles, the framework addresses threats across training, deployment, inference, and post-deployment monitoring. It also considers geopolitical risks, model misuse, and data poisoning, offering strategies such as secure compute environments, verifiable datasets, continuous validation, and runtime assurance. The paper proposes a roadmap for governments, enterprises, and developers to collaboratively build trustworthy AI systems for critical applications.Download this free whitepaper now!
