Abstract

Cloud sovereignty, data residency, confidential computing, and workload identity mechanisms increasingly govern how artificial intelligence systems, distributed applications, and autonomous agents operate across geographic and regulatory boundaries. However, authorization obtained within one jurisdiction may remain technically valid after a workload is migrated, replicated, delegated, or failed over into another jurisdiction. Valid OAuth credentials, workload identity tokens, hardware attestation, encrypted communications, and regional deployment controls do not independently establish that the jurisdiction applicable at the moment of execution still satisfies the original authorization.

This technical disclosure presents a jurisdiction-aware execution authorization and enforcement architecture for sovereign AI infrastructure, multi-cloud environments, confidential computing, cross-border data processing, and distributed autonomous systems.

The disclosed method introduces the following technical controls:

  1. Pre-execution containment: A proposed operation remains non-effective until the applicable jurisdictional and operational requirements are validated at a mandatory enforcement boundary.
  2. Multi-dimensional jurisdiction policy: Machine-readable authorization constraints cover processing location, data residency, storage boundaries, operator control, cryptographic key custody, remote administration, destination restrictions, and platform trust conditions.
  3. Protected evidence-based verification: Trusted infrastructure evidence establishes the current execution context using independently verifiable inputs, including workload identity, remote attestation, infrastructure state, and policy metadata.
  4. Execution-time jurisdiction validation: A protected enforcement component verifies that the actual execution environment satisfies the original jurisdiction restrictions, rather than relying exclusively on previously issued credentials or deployment configuration.
  5. State-change and failover detection: Versioned state indicators and generation counters detect changes in processing region, infrastructure ownership or control, key custody, administrative access, and other jurisdiction-relevant conditions between authorization and execution.
  6. Atomic authorization and effectuation: The final enforcement boundary performs a freshness and policy-consistency check immediately before committing the operation, preventing stale or mismatched authorization from enabling an unauthorized effect.
  7. Fail-closed and bypass-resistant enforcement: Missing, conflicting, outdated, or unverifiable jurisdiction evidence blocks execution. Enforcement coverage includes asynchronous workflows, cross-region replication, disaster-recovery failover, global management interfaces, and alternative execution paths.

The architecture complements OAuth 2.0 Rich Authorization Requests (RFC 9396), IETF Remote ATtestation procedureS (RATS), Workload Identity in Multi-System Environments (WIMSE), Supply Chain Integrity, Transparency, and Trust (SCITT), trusted execution environments, confidential computing, and established cloud sovereignty mechanisms.

Industrial applicability includes sovereign-cloud services, AI inference hosting, GPU and accelerator infrastructure, autonomous AI agents, multi-cloud orchestration, cross-border financial transactions, regulated data processing, telecommunications, and critical infrastructure.

The disclosed contribution is the binding of jurisdiction-specific authorization to the verified infrastructure state and actual execution boundary, rather than treating geographic deployment, workload authentication, or prior authorization as sufficient evidence of continuing execution authority.

The method enforces explicitly configured jurisdiction policies; it does not independently determine legal compliance. Its security properties depend on trustworthy evidence, protected enforcement, atomic state validation, and complete coverage of consequential execution paths.

Full technical disclosure, formal model, implementation workflow, and five visual flowcharts:

https://zenodo.org/records/23686175

Keywords: Sovereign AI; AI Governance; Cloud Sovereignty; Data Sovereignty; Data Residency; Jurisdiction-Aware Access Control; Cross-Border Data Processing; Execution-Time Authorization; Policy Enforcement Point (PEP); Zero Trust Architecture; Confidential Computing; Trusted Execution Environment (TEE); Remote Attestation; Workload Identity; WIMSE; OAuth 2.0; SCITT; GPU Infrastructure Security; Multi-Cloud Security; Cross-Region Failover; Disaster Recovery; Distributed AI Agents; Secure AI Inference; Cryptographic Key Residency; Policy-as-Code; Time-of-Check-to-Time-of-Use (TOCTOU); Atomic Authorization; Infrastructure Security; Regulatory Compliance Automation.

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Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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