Secure Model Provenance

Definition

Secure Model Provenance is cryptographic and procedural evidence tracking where a model, adapter, dataset, or artifact came from. In defense applications, it prevents unknown weights or tampered adapters from entering operational systems. The hard part is broken signing chains and untracked emergency changes, especially when systems are deployed across contested links, coalition boundaries, and mixed human-machine teams. KhanBMS treats it as a required trust property for KhanBMS modular AI packages, tying the concept back to modular command, edge execution, and auditable authority.

Reference attributes

Layer

AI supply-chain control

Operational value

Prevents unknown weights or tampered adapters from entering operational systems

Primary risk

Broken signing chains and untracked emergency changes

KhanBMS role

A required trust property for KhanBMS modular AI packages

Related terms

• AI Bill of Materials (AIBOM)
  Inventory of models, datasets, adapters, tools, dependencies, licenses, and provenance in an AI system.
• Edge Model Registry
  Versioned catalog that tracks which models, adapters, signatures, and policies are deployed to tactical nodes.
• AI Supply Chain Security
  Protection of datasets, weights, code, dependencies, tooling, and deployment pipelines for AI systems.
• Confidential AI Computing
  Use of encryption, enclaves, and attestation to protect AI workloads while data is in use.