2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
Mingyuan Fan, Yu Liu, Fuyi Wang +1
The deployment of large language models (LLMs) on resource-constrained devices remains challenging, spurring interest in split inference, where models are partitioned between clien…
PrivGNN: High-Performance Secure Inference for Cryptographic Graph Neural Networks
Fuyi Wang, Zekai Chen, Mingyuan Fan +3
Graph neural networks (GNNs) are powerful tools for analyzing and learning from graph-structured (GS) data, facilitating a wide range of services. Deploying such services in privac…
FLAME: Flexible and Lightweight Biometric Authentication Scheme in Malicious Environments
Fuyi Wang, Fangyuan Sun, Mingyuan Fan +5
Privacy-preserving biometric authentication (PPBA) enables client authentication without revealing sensitive biometric data, addressing privacy and security concerns. Many studies…
CCJA: Context-Coherent Jailbreak Attack for Aligned Large Language Models
Guanghao Zhou, Panjia Qiu, Mingyuan Fan +4
Despite explicit alignment efforts for large language models (LLMs), they can still be exploited to trigger unintended behaviors, a phenomenon known as "jailbreaking." Current jail…