Definition
Cryptographic verification is the mathematical process of confirming three things about a piece of evidence: that it has not been altered (integrity, via hashing), that it was produced by the claimed party (authenticity, via digital signatures), and that the claimed party was authorized to produce it (authority, via key management).
It is the engine beneath independent verification. Because these checks rely on mathematics and public keys rather than trust, anyone can perform them and reach the same, reliable conclusion.
Why it matters
Cryptographic verification is what makes proof trustworthy without a trusted intermediary. It converts "believe me" into "check for yourself."
- It provides objective, repeatable confirmation anyone can perform.
- It underpins integrity, authenticity, and authorization simultaneously.
- It scales to machine speed, enabling automated and AI-driven verification.
- It relies on well-established, standardized cryptographic primitives.
Real-world examples
Checking a signature
A verifier confirms a proof’s ed25519 signature is valid for the issuer’s public key — establishing authenticity.
Recomputing a hash
Given the data, a verifier recomputes its hash and compares it to the artifact’s commitment to confirm integrity.
Confirming authority
The verifier checks that the signing key is authorized and active, confirming the issuer had the right to produce the proof.
Visual explanation
Frequently asked questions
Related concepts
Independent Verification
Independent verification is the ability for any party to confirm that an event or claim is true using mathematics, without trusting the party that produced the evidence.
Read articleEvidence Integrity
Evidence integrity is the guarantee that a record has not been altered, reordered, or fabricated since the event it describes actually occurred.
Read articleProof Artifact
A proof artifact is a compact, cryptographically signed record that commits to a business or AI event so it can be independently verified without exposing the underlying data.
Read articleAI Accountability
AI accountability is the ability to prove what an AI system did, when, on what basis, and under whose authority — so that AI actions can be verified and answered for.
Read articleRelated questions
Related comparisons
See it in action
Inspect a proof artifact and run independent verification in the live demo.