trusted execution for ml

**Trusted Execution for ML** is the **use of hardware-based Trusted Execution Environments (TEEs) to protect ML models and data during computation** — processing sensitive data and model inference inside a secure, hardware-isolated enclave that even the host operating system cannot access. **TEE Technologies** - **Intel SGX**: Intel's Software Guard Extensions — create encrypted enclaves in memory. - **ARM TrustZone**: ARM's security extension — partition processor into secure and non-secure worlds. - **AMD SEV**: Secure Encrypted Virtualization — encrypt VM memory with hardware keys. - **Confidential Computing**: Cloud providers offer TEE-based VMs for secure ML inference. **Why It Matters** - **Data-in-Use Protection**: Unlike encryption (which protects data at rest and in transit), TEEs protect data during computation. - **Model Protection**: The model is decrypted only inside the TEE — prevents model extraction by the cloud provider. - **Attestation**: Remote attestation proves to clients that their data is processed inside a genuine TEE. **Trusted Execution** is **hardware-secured computation** — using isolated, encrypted processor enclaves to protect both models and data during ML inference.