SHA3-256 Fingerprint 3 PQ Signatures Independent Verification

Verifiable Computation

You computed something expensive. The consumer needs to know the result is correct.
Prove it without re-executing. Verify at 31 nanoseconds.

31ns
Verification Lookup
3
PQ Signature Families
0
Re-Executions Needed
96ns
Fingerprint Compute
Definition

Verifiable computation is the ability to prove that a computation was performed correctly without requiring the verifier to re-execute it. The prover attaches a computation fingerprintSHA3-256(input || computation || parameters || version || hardware) — to the result. The result is signed by three independent post-quantum signature families. The verifier checks the fingerprint and signatures. If they match, the result is correct. No re-execution. No trust assumption. 31 nanoseconds.

The Problem

How Do You Know the Result Is Correct?

You receive a computation result from another system. An ML inference score. A risk calculation. A compliance check. A financial aggregation. How do you know the result is correct?

Today, you have three options. All of them are inadequate.

Approaches

Three Ways to Verify. Only One Scales.

Re-Computation
2x cost
Run the same computation again Compare outputs Doubles your compute bill Does not scale
Trusted Third Party
Trust
Delegate verification to auditor Single point of trust Auditor can be compromised Adds latency and cost
Cachee Fingerprint
31ns
SHA3-256 binds result to inputs 3 PQ families sign the result Verify without re-executing No trust assumption

Re-computation doubles your cost. Trusted third parties add a trust assumption. Cachee's computation fingerprint proves correctness at 31 nanoseconds with zero re-execution and zero trust in the prover.

How It Works

The Computation Fingerprint

A computation fingerprint is a deterministic hash that uniquely identifies a computation result by binding it to everything that produced it. It is a content address — the address IS the proof.

fingerprint = SHA3-256( input_data // the exact input bytes || computation_type // "ml_inference", "risk_calc", etc. || parameters // model version, thresholds, config || software_version // exact binary hash || hardware_id // platform identifier ) // The fingerprint is deterministic: // Same inputs + same computation = same fingerprint. Always. // Different input (even 1 bit) = completely different fingerprint.

Two independent systems running the same computation on the same inputs will produce the same fingerprint. This is the basis of verifiability. You do not need to trust the prover. You verify the fingerprint. These results don't live in isolation — they become a tamper-proof audit trail.

Pipeline

The Verification Flow

From computation to verified result in five steps.

🖥
Compute
Run the computation on input data
🔏
Fingerprint
SHA3-256(input || comp || params || ver)
🔒
Sign
ML-DSA + FALCON + SLH-DSA
📦
Cache
Store result + fingerprint + signatures
🔍
Verify
Check fingerprint + check signatures
Verified
31ns from cache
Attestation

Signed Results: Three PQ Families

A fingerprint proves what was computed. Signatures prove who computed it and that it has not been modified. Every cached result is signed by three independent post-quantum signature families:

FamilyAlgorithmBasisSignature SizeNIST Level
Lattice (MLWE)ML-DSA-65Module lattices3,309 bytesLevel 3
Lattice (NTRU)FALCON-512NTRU lattices656 bytesLevel 1
Hash-basedSLH-DSAStateless hashes17,088 bytesLevel 1

Forging a result requires breaking MLWE lattices, NTRU lattices, AND stateless hash functions simultaneously — three independent mathematical assumptions. This is not defense in depth. It is mathematical redundancy. This is the foundation of verifiable audit infrastructure.

Comparison

Cachee Fingerprints vs ZK Proofs

Both prove computation correctness. They serve different purposes.

Zero-Knowledge Proofs

Privacy
Hides inputs, reveals truth

Proves a statement without revealing data. Requires circuit compilation, trusted setup (SNARKs), or FRI protocol (STARKs). Verification: 1ms-25us. Proof generation: seconds to minutes. Use when you need input privacy.

Cachee Computation Fingerprint

31ns
Binds result to inputs, proves execution

Proves a computation was executed correctly on specific inputs. No circuit compilation. No trusted setup. SHA3-256 hash + PQ signatures. Verification: 31ns from cache. Use when you need proof of correct execution, not input privacy.

PropertyZK ProofsCachee Fingerprints
Input PrivacyYes (hidden)No (inputs bound)
Proof GenerationSeconds to minutes96ns (SHA3-256)
Verification1ms - 25us31ns from cache
Setup RequiredCircuit compilationNone
Post-QuantumDepends on schemeYes (3 PQ families)
Proof Size200B - 100KB32 bytes (fingerprint)

If you need to prove "I know X without revealing X," use ZK proofs. If you need to prove "this result was correctly computed from these inputs," use Cachee. They are complementary — and Cachee can cache ZK verification results at 85ns.

Trust Model

Independent Verification

The verification is independent. You do not need a Cachee account, a network connection, or trust in H33 to verify a computation result. The cachee-verify tool is a standalone binary that checks:

All four checks must pass. If any one fails, the result is rejected. The verification is offline, deterministic, and takes 31 nanoseconds from cache.

cachee-verify-demo
[1] $ cachee set risk:portfolio_47 '{"score":0.73}' \
    FP compute=risk_model input=portfolio_47 ver=2.1.0
    OK fingerprint=0x8a2f...c317 signed=3/3 PQ
 
[2] $ cachee-verify risk:portfolio_47
    Fingerprint: MATCH (recomputed from inputs)
    ML-DSA-65: VALID
    FALCON-512: VALID
    SLH-DSA: VALID
 
    VERIFIED in 31ns. No re-execution. No network. No trust.

Run it yourself: brew install cachee && cachee verify-demo

Performance

Re-Computation vs Cached Verification

A typical ML inference takes 10ms. Verifying via re-computation takes another 10ms. Verifying via Cachee takes 31 nanoseconds.

Re-computation verification (run the same model again) 10,000,000 ns (10ms)
Full re-execution of the computation
Cachee verification (fingerprint + signature check) 31 ns
322,580x
Same correctness guarantee. No re-execution. The fingerprint IS the proof.
Applications

Where Verifiable Computation Matters

🤖
ML Inference Results
A model scores a risk. Downstream systems need to trust that score without re-running the model. The fingerprint binds the score to the model version, input features, and parameters.
💰
Financial Calculations
NAV computations, risk aggregations, margin calculations. Auditors need proof the numbers are correct. The fingerprint provides cryptographic proof without re-running the calculation.
Compliance Checks
A compliance engine evaluates a transaction. The result — approved or flagged — is fingerprinted and signed. Regulators verify the check was performed correctly without re-executing it.
🔬
Scientific Computation
Simulation results, genomic analyses, climate models. Reproducibility crises end when every result carries a computation fingerprint that proves exactly what was computed.
🔗
Cross-System Data Sharing
System A computes a result. System B consumes it. Without verifiable computation, System B must either re-compute or blindly trust. With Cachee, System B verifies in 31ns.
📦
Supply Chain Verification
Quality scores, inspection results, test outcomes. Each computation is fingerprinted at the point of creation. Every downstream consumer can independently verify.
Install

Get Started

brew tap h33ai-postquantum/tap && brew install cachee cachee init && cachee start # Store a computation result with fingerprint SET result:calc_789 '{"value":42.7}' FP compute=aggregation input=dataset_A ver=1.3.0 # Verify the result (offline, no network) cachee-verify result:calc_789 # Retrieve verified result at 31ns GETVERIFIED result:calc_789

Every SET is automatically fingerprinted and PQ-signed. The FP flag adds the computation fingerprint binding. GETVERIFIED returns the result only if signatures are valid. Zero additional infrastructure. Every output is tied to its origin through data lineage verification.

Compute once. Prove forever. Verify at 31 nanoseconds.

Install Cachee Computation Fingerprinting

Deep Dives

Knowledge Base

Explore Verifiable Computation Infrastructure

Every page in the Cachee knowledge base. Proven computation, not cached data.

Post-Quantum Caching
The category definition. Run computation once, serve forever.
Computation Fingerprinting
Identity for results. Provenance, not just output.
Cache Attestation
Signed cache entries. Three PQ families per SET.
ZK Caching
Cache STARK and SNARK verification results at 85ns.
Tamper-Proof Audit Trails
SHA3-256 hash-chained immutable logging.
Compliance-Ready Infrastructure
Pass audits without slowing down.