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cs.CR2026
Understanding the Security Boundary of Obfuscation-based On-Device LLM Protection
Hanyi Zhou, Chenyang Li, Yuanzhe Pang +3
Trusted Execution Environments (TEEs) offer a promising mechanism for safeguarding the intellectual property of on-device Large Language Models (LLMs). To overcome the inherent com…
cs.CR2026
Blind Gods and Broken Screens: Architecting a Secure, Intent-Centric Mobile Agent Operating System
Zhenhua Zou, Sheng Guo, Qiuyang Zhan +6
The evolution of Large Language Models (LLMs) has shifted mobile computing from App-centric interactions to system-level autonomous agents. Current implementations predominantly re…
cs.CR2024
Pencil: Private and Extensible Collaborative Learning without the Non-Colluding Assumption
Xuanqi Liu, Zhuotao Liu, Qi Li +2
The escalating focus on data privacy poses significant challenges for collaborative neural network training, where data ownership and model training/deployment responsibilities res…