A secure data pipeline for transferring sensitive data from cloud to local GPU processing
You have sensitive data (medical images, confidential documents, research data) stored in the cloud. You need to process it on your local GPU workstation. How do you transfer it securely?
Traditional approaches leave data vulnerable:
- Cloud providers can access unencrypted data
- Data sits decrypted during processing
- No audit trail for compliance (HIPAA, GDPR)
- Sensitive files left on disk after processing
┌─────────────────────────────────────────────────────────────────────────────┐
│ │
│ [Hospital/Cloud] ══════════════► [Your GPU Workstation] │
│ │ │
│ ┌─────┴─────┐ │
│ │ ENCRYPTED │ │
│ │ SECURE │ │
│ │ PIPELINE │ │
│ └───────────┘ │
│ │
│ • Data encrypted BEFORE leaving source │
│ • Keys NEVER leave your workstation │
│ • Decryption ONLY on your local machine │
│ • Audit trail for compliance │
│ • Secure deletion after processing │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Secure Media Processor is a secure pipeline that ensures sensitive data is protected at every stage—from cloud storage to local GPU processing and cleanup.
- AES-256-GCM authenticated encryption
- ECDH key exchange for multi-party transfers
- Zero-knowledge mode — cloud provider never sees plaintext
- AWS S3
- Google Drive
- Dropbox
- Azure Blob Storage (coming soon)
- HIPAA/GDPR compliant audit logging
- Immutable audit trail with cryptographic verification
- Configurable retention policies
- Multi-pass secure deletion (DoD 5220.22-M)
- Encrypted key storage
- Checksum verification on all transfers
pip install secure-media-processorfrom secure_media_processor import Pipeline, TransferMode
# Initialize secure pipeline
pipeline = Pipeline(
encryption_key="~/.smp/keys/master.key",
audit_log="~/.smp/audit/"
)
# Add your cloud source
pipeline.add_source('hospital', S3Connector(
bucket_name='patient-scans',
region='us-east-1'
))
# Secure download to local GPU workstation
manifest = pipeline.secure_download(
source='hospital',
remote_path='mri-scans/patient-001/',
local_path='/secure/gpu-workspace/',
mode=TransferMode.ZERO_KNOWLEDGE # Maximum security
)
# Verify data integrity
assert pipeline.verify_integrity(manifest)
# Process locally on your GPU (your code here)
results = your_ml_model.process(manifest.destination)
# Secure cleanup when done
pipeline.secure_delete(manifest.destination)- Medical researchers processing patient MRI/CT scans
- Healthcare organizations meeting HIPAA requirements
- Research institutions handling sensitive data
- Anyone who needs to securely move data to GPU for processing
secure-media-processor/
├── src/
│ ├── core/ # Core pipeline functionality
│ │ ├── secure_transfer.py # Main transfer pipeline
│ │ ├── encryption.py # AES-256-GCM encryption
│ │ ├── audit_logger.py # Compliance logging
│ │ └── key_exchange.py # ECDH key exchange
│ ├── connectors/ # Cloud storage connectors
│ │ ├── s3_connector.py
│ │ ├── google_drive_connector.py
│ │ └── dropbox_connector.py
│ └── cli.py # Command-line interface
├── plugins/ # Optional processing plugins
│ └── smp_medical/ # Medical imaging plugin
└── docs/ # Documentation
├── architecture/
├── api/
└── examples/
The core package focuses on secure data transfer. Domain-specific processing is handled by optional plugins:
# Medical imaging (DICOM, U-Net segmentation)
pip install secure-media-processor[medical]
# Video processing (coming soon)
pip install secure-media-processor[video]Plugins process data locally after it has been securely transferred.
- Security Model — Threat model, encryption details
- Data Flow — How data moves through the pipeline
- Pipeline API — Core API reference
- Examples — Working code examples
| Stage | Protection |
|---|---|
| At rest (cloud) | AES-256-GCM encryption |
| In transit | AES-256-GCM + TLS |
| At rest (local) | Encrypted with master key |
| Processing | Decrypted only in memory |
| Cleanup | Multi-pass secure deletion |
Zero-Knowledge Transfer: In this mode, data is encrypted at the source (e.g., hospital) using a shared key derived via ECDH. The cloud provider never has access to the plaintext or decryption keys.
- Audit logging with 6-year retention
- Access controls (local-only decryption)
- Encryption meets requirements
- Data minimization support
- Right to erasure (secure deletion)
- Complete audit trail
# Encrypt a file locally
smp encrypt sensitive-data.dcm encrypted.bin
# Download from cloud (decrypts locally)
smp download s3://bucket/path/file.enc ./local-file.dcm
# Secure delete
smp delete --secure ./sensitive-data.dcm
# View system info
smp info- Core secure transfer pipeline
- ECDH key exchange
- HIPAA-compliant audit logging
- Plugin architecture
- Streaming transfer for large files
- Azure Blob Storage connector
- Docker containerization
- REST API server
- Web dashboard
- Hardware Security Module (HSM) integration
We welcome contributions! See CONTRIBUTING.md.
Priority areas:
- Additional cloud connectors
- Performance optimization
- Security auditing
Security is the core mission. If you discover a vulnerability, please see our Security Policy for responsible disclosure.
MIT License — see LICENSE.
Secure Media Processor — Your data, your GPU, your control.
Built for researchers who need security without compromise.