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Securing the Future of AI Through Rigorous Safety, Resilience, and Zero-Trust Design Principles
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.
What Attendees will Learn
- How zero-trust security protects AI systems from attacks
- Methods to reduce hallucinations (RAG, fine-tuning, guardrails)
- Best practices for resilient AI deployment
- Key AI security standards and frameworks
- Importance of open-source and explainable AI
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IEEE Spectrum and Wiley are proud to bring you this white paper, sponsored by Technology Innovation Institute.
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The Technology Innovation Institute (TII) is a leading research organization that focuses on developing cutting-edge technologies to solve real-world problems.
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IEEE Spectrum Magazine, the flagship publication of the IEEE, explores the development, applications and implications of new technologies. It anticipates trends in engineering, science, and technology, and provides a forum for understanding, discussion and leadership in these areas.