Understanding the Security Boundary of Obfuscation-Based On-Device LLM Protection

Trusted Execution Environments TEEs offer a promising mechanism for safeguarding the intellectual property of on-device Large Language Models LLMs. To overcome the inherent computational bottlenecks of TEEs, existing TEE-Shielded LLM Partition TSLP methods apply efficient obfuscation schemes to...

Vulnerabilities in Partial TEE-Shielded LLM Inference with Precomputed Noise

The deployment of large language models LLMs on third-party devices requires new ways to protect model intellectual property. While Trusted Execution Environments TEEs offer a promising solution, their performance limits can lead to a critical compromise: using a precomputed, static secret basis ...