Trusted Execution Environment

Trusted Execution Environments (TEEs) are isolated hardware regions designed to protect sensitive computations and data from untrusted software and hardware. Current research focuses on improving TEE performance and security for machine learning applications, particularly large language models (LLMs) and federated learning, often employing techniques like model slicing, homomorphic encryption, and novel neural architectures to mitigate performance overhead while enhancing privacy and integrity. This work is significant because it addresses critical security and privacy challenges in increasingly prevalent cloud-based and distributed computing scenarios, enabling secure collaboration and the development of trustworthy AI systems.