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Synthetic Data Certification

How synthetic dataset certification works: SHA-256 hashing, Ed25519 signatures, machine-verifiable certification records, and EU AI Act compliance.

Synthetic data certification is the process of cryptographically attesting that a synthetic dataset was generated according to documented parameters, passes validation criteria, and has not been tampered with since certification.

Certification records link the dataset to its generation configuration, validation results, timestamp, and issuing organization — creating a tamper-evident audit trail that can be independently verified.

This is increasingly required for AI systems subject to EU AI Act Article 10 (training data requirements), Article 12 (logging), and sector-specific AI governance policies in finance, healthcare, and government.

How Cryptographic Certification Works

A certification authority hashes the synthetic dataset using SHA-256 to produce a unique fingerprint. This fingerprint is then signed with Ed25519 — an elliptic curve signature algorithm — using the authority's private key. The resulting signature, combined with the dataset hash and generation metadata, forms the certification artifact. Any modification to the dataset — however minor — produces a different hash, invalidating the signature.

CertifiedData.io provides cryptographic certification infrastructure for synthetic datasets and AI artifacts, producing tamper-evident records for audit and EU AI Act compliance.

What a Certification Record Contains

A standard synthetic data certification record includes: dataset identifier, SHA-256 hash, generation parameters (model, seed, configuration), validation scores, certification timestamp, issuer identity, Ed25519 public key (for verification), and certification expiry policy.

EU AI Act and Certification

EU AI Act Article 10 requires that training, validation, and testing data used in high-risk AI systems be subject to appropriate data governance practices. Certified synthetic datasets, with documented generation and validation provenance, directly satisfy these requirements and enable efficient audit response.

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