Technical Whitepaper24 pagesPublished December 2025

Post-Quantum Cryptographic Proof for AI Sovereign Systems

Technical deep dive into cryptographic verification of AI model provenance, training data integrity, and inference authenticity using post-quantum algorithms. Essential reading for AI governance and compliance.

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Executive Brief

AI Sovereignty Requires Cryptographic Proof

As AI systems become critical infrastructure, organizations need cryptographic guarantees about model provenance, training data integrity, and inference authenticity. Without these guarantees, AI systems remain vulnerable to supply chain attacks, data poisoning, and model tampering.

This whitepaper presents a complete framework for AI sovereignty using post-quantum cryptographic proofs, ensuring your AI systems remain secure and auditable in the quantum computing era.

ML-DSA

Signatures

NIST standard

Immutable

Audit Trail

Training records

Zero-Trust

Architecture

Verified inference

EU AI Act

Compliant

Ready framework

What's Inside the Full Whitepaper

AI Supply Chain Security

Cryptographic verification of model origins and training pipeline integrity.

Training Data Provenance

Immutable records of data sources, preprocessing, and augmentation steps.

Model Signature Schemes

Post-quantum digital signatures for model weights and architectures.

Inference Attestation

Real-time cryptographic proofs that inference used authorized models.

Compliance Integration

Alignment with EU AI Act, NIST AI RMF, and industry standards.

Implementation Architecture

Reference architecture for production AI sovereignty systems.