🔒Use Cases

TEE provide hardware-based isolation for sensitive computations, ensuring data confidentiality and integrity. This document explores various use cases where TEEs can be combined with other technologies to create powerful, secure solutions.

TEE + AI

TEEs can protect AI model training and inference, preserving both model privacy and data confidentiality. This combination enables secure machine learning on sensitive data while preventing unauthorized access to proprietary models.

TEE also can be used to build unruggable AI Agents that operate with the same level of trustworthiness as smart contracts, check the article by Phala CEO Marvin Tong to see why we get there.

Check out Building Confidential AI with TEE

TEE + FHE/MPC

TEEs can complement Fully Homomorphic Encryption (FHE) and Multi-Party Computation (MPC) to create hybrid systems with enhanced performance and security guarantees. These combinations allow for secure computation on encrypted data with reduced overhead.

Check out TEE with FHE and MPC

TEE + ZK/ZKrollup

When combined with Zero-Knowledge Proofs (ZK) and ZK-Rollups, TEEs can enable efficient verification of computations while maintaining privacy. This approach is particularly valuable for blockchain applications requiring both scalability and confidentiality.

Check out TEE with ZK and ZKrollup