NIST OLIR: Invariant Reality Prism (IRP) - Set Theory Mapping for High-Assurance AI Systems [Version 2026-02-05]

Official Mapping for NIST OLIR Program inclusion. This dataset contains the structural mapping of the Invariant Reality Prism (IRP), a Layer-0 deterministic control framework designed for High-Assurance AI Systems. The IRP enforces human sovereignty by applying an Invariant Operational Boundary Rsov=1 to AI agents and quantum simulations. Technical Scope: > This version is specifically mapped against the NIST Cybersecurity Framework (CSF) 2.0. It defines deterministic supersets over probabilistic controls, ensuring a "Fail-Closed" state in the event of information entropy or mission-critical deviation. Validation: > Validated by the NIST OLIR Program on February 5, 2026, for catalog inclusion as a Hybrid Technical Informative Reference.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-05
DOI
https://doi.org/10.5281/zenodo.18498447
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
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article

NIST OLIR: Invariant Reality Prism (IRP) - Set Theory Mapping for High-Assurance AI Systems [Version 2026-02-05]

Pablo Octavio Feria Hernández
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

NIST OLIR: Invariant Reality Prism (IRP) - Set Theory Mapping for High-Assurance AI Systems [Version 2026-02-05]

Pablo Octavio Feria Hernández
article en

Abstract

Official Mapping for NIST OLIR Program inclusion. This dataset contains the structural mapping of the Invariant Reality Prism (IRP), a Layer-0 deterministic control framework designed for High-Assurance AI Systems. The IRP enforces human sovereignty by applying an Invariant Operational Boundary Rsov=1 to AI agents and quantum simulations. Technical Scope: > This version is specifically mapped against the NIST Cybersecurity Framework (CSF) 2.0. It defines deterministic supersets over probabilistic controls, ensuring a "Fail-Closed" state in the event of information entropy or mission-critical deviation. Validation: > Validated by the NIST OLIR Program on February 5, 2026, for catalog inclusion as a Hybrid Technical Informative Reference.

Zenodo (CERN European Organization for Nuclear Research)
Prudential Financial (United States) (US)
Reduced inequalities
Openalex Percentile: Top 67%
Adversarial Robustness in Machine Learning
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