2 papers
cs.CR2026
Towards Privacy-Preserving LLM Inference via Covariant Obfuscation (Technical Report)
Yu Lin, Qizhi Zhang, Wenqiang Ruan +6
The rapid development of large language models (LLMs) has driven the widespread adoption of cloud-based LLM inference services, while also bringing prominent privacy risks associat…
cs.CR2025
OFL: Opportunistic Federated Learning for Resource-Heterogeneous and Privacy-Aware Devices
Yunlong Mao, Mingyang Niu, Ziqin Dang +7
Efficient and secure federated learning (FL) is a critical challenge for resource-limited devices, especially mobile devices. Existing secure FL solutions commonly incur significan…