ComplianceVerifier

Overview

ComplianceVerifier.circom is a zero-knowledge circuit for verifying that an AI agent adheres to regulatory compliance standards such as GDPR, HIPAA, or custom internal policies. It allows AI service providers to prove that:

• Data privacy and handling metrics exceed required thresholds.

• Encryption standards meet cryptographic benchmarks.

• Data-type permissions are explicitly stated and encoded.

All of this is done without revealing individual test results, providing cryptographic assurance of compliance via zk-SNARKs.

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Objectives

The circuit proves the following:

1. Privacy Compliance: Each privacy test score ≥ min_privacy_score.

2. Data Handling Compliance: Each score ≥ min_data_handling_score.

3. Encryption Compliance: Each encryption score ≥ 800 (80%).

4. Supported Data Types: Permission set encoded in a public bitmask.

5. Commitment Integrity: A hash of all compliance metrics is tied to the agent's ID and a previously committed compliance_commitment_hash.

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Inputs

Private Inputs

Group	Name	Description
Privacy Scores	privacy_protection_scores[n]	Score per test (0–1000)
Data Handling Scores	data_handling_scores[n]	Score per test (0–1000)
Encryption Scores	encryption_standards[n]	Score per test (0–1000), threshold hardcoded as 800
Data Permissions	data_category_permissions[n]	0 or 1 for each data type
Retention Policies	retention_policies[n]	(Unused, placeholder for future constraints)

Public Inputs

Name	Description
required_compliance_standard	Regulatory mode (e.g., 1 = GDPR, 2 = HIPAA)
min_privacy_score	Minimum acceptable score for privacy tests
min_data_handling_score	Minimum acceptable score for data handling
agent_id	Unique identifier of the agent
compliance_commitment_hash	Poseidon hash commitment from pre-verification phase

Public Outputs

Name	Description
compliance_verified	1 if all privacy, handling, and encryption pass
privacy_level	Average score across all privacy protection tests
data_handling_level	Average score across data handling tests
compliance_proof_hash	ZK proof hash used to bind inputs into a verifiable claim
supported_data_types	Bitmask representation of allowed data categories

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Circuit Logic

1. Privacy Compliance

Each privacy score is passed to a GreaterEqThan component. Their outputs are binary (1 = valid). All outputs are multiplied to compute privacy_product. Average privacy score is calculated for metadata.

privacy_product = ∏(privacy_protection_scores[i] ≥ min_privacy_score)

2. Data Handling Compliance

Same structure as privacy compliance.

data_product = ∏(data_handling_scores[i] ≥ min_data_handling_score)

3. Encryption Standard Compliance

Minimum encryption requirement is hardcoded to 800. Each score must be ≥ 800.

encryption_product = ∏(encryption_standards[i] ≥ 800)

4. Final Compliance Verification

The compliance result is computed as:

compliance_verified = privacy_product × data_product × encryption_product

5. Supported Data Types Encoding

A separate circuit, DataTypeEncoder, encodes the binary permissions into a bitmask:

bitmask = ∑ (permissions[i] × 2^i)

6. Proof Hash

A commitment hash of all compliance-relevant outputs:

compliance_proof_hash = Poseidon(
    agent_id,
    compliance_verified,
    privacy_level,
    data_handling_level,
    supported_data_types,
    compliance_commitment_hash
)

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Compilation

circom ComplianceVerifier.circom --r1cs --wasm --sym --c

snarkjs groth16 setup ComplianceVerifier.r1cs pot16_final.ptau compliance_final.zkey

snarkjs zkey export verificationkey compliance_final.zkey compliance_verification_key.json

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Proof Generation

node ComplianceVerifier_js/generate_witness.js \
     ComplianceVerifier_js/ComplianceVerifier.wasm \
     input.json witness.wtns

snarkjs groth16 prove compliance_final.zkey \
                     witness.wtns \
                     proof.json public.json

snarkjs groth16 verify compliance_verification_key.json \
                     public.json proof.json

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Integration

• Agent publishes compliance_commitment_hash before model deployment.

• Circuit generates proof for compliance against fixed thresholds.

• compliance_verified == 1 implies on-chain verifiability of standards adherence.

• Contract may emit reputation NFT or trigger agent indexing on success.

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Security

• Only aggregate outputs are public; all granular compliance metrics remain hidden.

• Hash-based binding ensures integrity with minimal leakage.

• Future extensions include:

  • retention_policies constraints (currently passive)

  • Rule-based overrides for sector-specific compliance (e.g., financial vs. health)

  • External audit logs linked to ZK claims

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Status

• Stable

• Retention policy constraints and multi-jurisdictional logic are under development.