3 papers
cs.CR2026
FuseFSS: Efficient Secure LLM Inference with Function Secret Sharing
Yuhan Ma, Yong Li, Stefan Schmid
Two-server secure inference allows a client to query a hosted large language model (LLM) without revealing prompts or embeddings. Recent GPU systems based on function secret sharin…
cs.CR2026
SecureClaw: Clawing Back Control of LLM Agents
Yuhan Ma, Stefan Schmid
Tool-using large language model (LLM) agents face two distinct security failures: unauthorized external actions and exposure of sensitive plaintext inside the runtime before any fi…
cs.LG2026
Are LLM-Enhanced Graph Neural Networks Robust against Poisoning Attacks?
Yuhang Ma, Jie Wang, Zheng Yan
Large Language Models (LLMs) have advanced Graph Neural Networks (GNNs) by enriching node representations with semantic features, giving rise to LLM-enhanced GNNs that achieve nota…