A Minimal Common Assurance Architecture for Stateful AI Systems

This Technical Note proposes a minimal common assurance architecture for stateful AI systems. The proposal does not replace existing security practices or introduce a new security standard. Instead, it asks whether existing and future defensive mechanisms may become easier to connect, inspect, extend, replace, and evaluate if several assurance relationships are made explicit within a shared architectural skeleton. The architecture highlights evidence provenance and independence, AI-to-AI auditing, authorization and delegation, recovery validation, and human auditability. It is presented as a provisional framing for discussion, testing, criticism, modification, extension, simplification, or rejection where appropriate.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-30
DOI
https://doi.org/10.5281/zenodo.23061143
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
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A Minimal Common Assurance Architecture for Stateful AI Systems

Tetsuya Hiraku
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

A Minimal Common Assurance Architecture for Stateful AI Systems

Tetsuya Hiraku
article en

Abstract

This Technical Note proposes a minimal common assurance architecture for stateful AI systems. The proposal does not replace existing security practices or introduce a new security standard. Instead, it asks whether existing and future defensive mechanisms may become easier to connect, inspect, extend, replace, and evaluate if several assurance relationships are made explicit within a shared architectural skeleton. The architecture highlights evidence provenance and independence, AI-to-AI auditing, authorization and delegation, recovery validation, and human auditability. It is presented as a provisional framing for discussion, testing, criticism, modification, extension, simplification, or rejection where appropriate.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 9%
Adversarial Robustness in Machine Learning
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