- Add Prometheus metrics for marketplace API throughput and error rates with new dashboard panels - Implement confidential transaction models with encryption support and access control - Add key management system with registration, rotation, and audit logging - Create services and registry routers for service discovery and management - Integrate ZK proof generation for privacy-preserving receipts - Add metrics instru
10 KiB
10 KiB
Confidential Transactions Architecture
Overview
Design for opt-in confidential transaction support in AITBC, enabling participants to encrypt sensitive transaction data while maintaining selective disclosure and audit capabilities.
Architecture
Encryption Model
Hybrid Encryption with Envelope Pattern:
- Data Encryption: AES-256-GCM for transaction data
- Key Exchange: X25519 ECDH for per-recipient key distribution
- Envelope Pattern: Random DEK per transaction, encrypted for each authorized party
Key Components
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ Transaction │───▶│ Encryption │───▶│ Storage │
│ Service │ │ Service │ │ Layer │
└─────────────────┘ └──────────────────┘ └─────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ Key Manager │ │ Access Control │ │ Audit Log │
└─────────────────┘ └──────────────────┘ └─────────────────┘
Data Flow
1. Transaction Creation (Opt-in)
# Client requests confidential transaction
transaction = {
"job_id": "job-123",
"amount": "1000",
"confidential": True,
"participants": ["client-456", "miner-789", "auditor-001"]
}
# Coordinator encrypts sensitive fields
encrypted = encryption_service.encrypt(
data={"amount": "1000", "pricing": "details"},
participants=transaction["participants"]
)
# Store with encrypted payload
stored_transaction = {
"job_id": "job-123",
"public_data": {"job_id": "job-123"},
"encrypted_data": encrypted.ciphertext,
"encrypted_keys": encrypted.encrypted_keys,
"confidential": True
}
2. Data Access (Authorized Party)
# Miner requests access to transaction data
access_request = {
"transaction_id": "tx-456",
"requester": "miner-789",
"purpose": "settlement"
}
# Verify access rights
if access_control.verify(access_request):
# Decrypt using recipient's private key
decrypted = encryption_service.decrypt(
ciphertext=stored_transaction.encrypted_data,
encrypted_key=stored_transaction.encrypted_keys["miner-789"],
private_key=miner_private_key
)
3. Audit Access (Regulatory)
# Auditor with court order requests access
audit_request = {
"transaction_id": "tx-456",
"requester": "auditor-001",
"authorization": "court-order-123"
}
# Special audit key escrow
audit_key = key_manager.get_audit_key(audit_request.authorization)
decrypted = encryption_service.audit_decrypt(
ciphertext=stored_transaction.encrypted_data,
audit_key=audit_key
)
Implementation Details
Encryption Service
class ConfidentialTransactionService:
"""Service for handling confidential transactions"""
def __init__(self, key_manager: KeyManager):
self.key_manager = key_manager
self.cipher = AES256GCM()
def encrypt(self, data: Dict, participants: List[str]) -> EncryptedData:
"""Encrypt data for multiple participants"""
# Generate random DEK
dek = os.urandom(32)
# Encrypt data with DEK
ciphertext = self.cipher.encrypt(dek, json.dumps(data))
# Encrypt DEK for each participant
encrypted_keys = {}
for participant in participants:
public_key = self.key_manager.get_public_key(participant)
encrypted_keys[participant] = self._encrypt_dek(dek, public_key)
# Add audit escrow
audit_public_key = self.key_manager.get_audit_key()
encrypted_keys["audit"] = self._encrypt_dek(dek, audit_public_key)
return EncryptedData(
ciphertext=ciphertext,
encrypted_keys=encrypted_keys,
algorithm="AES-256-GCM+X25519"
)
def decrypt(self, ciphertext: bytes, encrypted_key: bytes,
private_key: bytes) -> Dict:
"""Decrypt data for specific participant"""
# Decrypt DEK
dek = self._decrypt_dek(encrypted_key, private_key)
# Decrypt data
plaintext = self.cipher.decrypt(dek, ciphertext)
return json.loads(plaintext)
Key Management
class KeyManager:
"""Manages encryption keys for participants"""
def __init__(self, storage: KeyStorage):
self.storage = storage
self.key_pairs = {}
def generate_key_pair(self, participant_id: str) -> KeyPair:
"""Generate X25519 key pair for participant"""
private_key = X25519.generate_private_key()
public_key = private_key.public_key()
key_pair = KeyPair(
participant_id=participant_id,
private_key=private_key,
public_key=public_key
)
self.storage.store(key_pair)
return key_pair
def rotate_keys(self, participant_id: str):
"""Rotate encryption keys"""
# Generate new key pair
new_key_pair = self.generate_key_pair(participant_id)
# Re-encrypt active transactions
self._reencrypt_transactions(participant_id, new_key_pair)
Access Control
class AccessController:
"""Controls access to confidential transaction data"""
def __init__(self, policy_store: PolicyStore):
self.policy_store = policy_store
def verify_access(self, request: AccessRequest) -> bool:
"""Verify if requester has access rights"""
# Check participant status
if not self._is_authorized_participant(request.requester):
return False
# Check purpose-based access
if not self._check_purpose(request.purpose, request.requester):
return False
# Check time-based restrictions
if not self._check_time_restrictions(request):
return False
return True
def _is_authorized_participant(self, participant_id: str) -> bool:
"""Check if participant is authorized for confidential transactions"""
# Verify KYC/KYB status
# Check compliance flags
# Validate regulatory approval
return True
Data Models
Confidential Transaction
class ConfidentialTransaction(BaseModel):
"""Transaction with optional confidential fields"""
# Public fields (always visible)
transaction_id: str
job_id: str
timestamp: datetime
status: str
# Confidential fields (encrypted when opt-in)
amount: Optional[str] = None
pricing: Optional[Dict] = None
settlement_details: Optional[Dict] = None
# Encryption metadata
confidential: bool = False
encrypted_data: Optional[bytes] = None
encrypted_keys: Optional[Dict[str, bytes]] = None
algorithm: Optional[str] = None
# Access control
participants: List[str] = []
access_policies: Dict[str, Any] = {}
Access Log
class ConfidentialAccessLog(BaseModel):
"""Audit log for confidential data access"""
transaction_id: str
requester: str
purpose: str
timestamp: datetime
authorized_by: str
data_accessed: List[str]
ip_address: str
user_agent: str
Security Considerations
1. Key Security
- Private keys stored in HSM or secure enclave
- Key rotation every 90 days
- Zero-knowledge proof of key possession
2. Data Protection
- AES-256-GCM provides confidentiality + integrity
- Random IV per encryption
- Forward secrecy with per-transaction DEKs
3. Access Control
- Multi-factor authentication for decryption
- Role-based access control
- Time-bound access permissions
4. Audit Compliance
- Immutable audit logs
- Regulatory access with court orders
- Privacy-preserving audit proofs
Performance Optimization
1. Lazy Encryption
- Only encrypt fields marked as confidential
- Cache encrypted data for frequent access
- Batch encryption for bulk operations
2. Key Management
- Pre-compute shared secrets for regular participants
- Use key derivation for multiple access levels
- Implement key caching with secure eviction
3. Storage Optimization
- Compress encrypted data
- Deduplicate common encrypted patterns
- Use column-level encryption for databases
Migration Strategy
Phase 1: Opt-in Support
- Add confidential flags to existing models
- Deploy encryption service
- Update transaction endpoints
Phase 2: Participant Onboarding
- Generate key pairs for all participants
- Implement key distribution
- Train users on privacy features
Phase 3: Full Rollout
- Enable confidential transactions by default for sensitive data
- Implement advanced access controls
- Add privacy analytics and reporting
Testing Strategy
1. Unit Tests
- Encryption/decryption correctness
- Key management operations
- Access control logic
2. Integration Tests
- End-to-end confidential transaction flow
- Cross-system key exchange
- Audit trail verification
3. Security Tests
- Penetration testing
- Cryptographic validation
- Side-channel resistance
Compliance
1. GDPR
- Right to encryption
- Data minimization
- Privacy by design
2. Financial Regulations
- SEC Rule 17a-4
- MiFID II transaction reporting
- AML/KYC requirements
3. Industry Standards
- ISO 27001
- NIST Cybersecurity Framework
- PCI DSS for payment data
Next Steps
- Implement core encryption service
- Create key management infrastructure
- Update transaction models and APIs
- Deploy access control system
- Implement audit logging
- Conduct security testing
- Gradual rollout with monitoring