5 papers
LLM agents security duality: a comprehensive survey of self-security and empowered cybersecurity
Yiwei Xu, Yong Zhuang, Xuanming Liu +6
Large language model (LLM) agents are rapidly being integrated into real-world systems. Their autonomy and tool-use capabilities generate substantial value while simultaneously exp…
AgentSentry: Mitigating Indirect Prompt Injection in LLM Agents via Temporal Causal Diagnostics and Context Purification
Tian Zhang, Yiwei Xu, Juan Wang +8
Large language model (LLM) agents increasingly rely on external tools and retrieval systems to autonomously complete complex tasks. However, this design exposes agents to indirect…
From Head to Tail: Efficient Black-box Model Inversion Attack via Long-tailed Learning
Ziang Li, Hongguang Zhang, Juan Wang +6
Model Inversion Attacks (MIAs) aim to reconstruct private training data from models, leading to privacy leakage, particularly in facial recognition systems. Although many studies h…
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning
Xiaoyang Xu, Mengda Yang, Wenzhe Yi +5
Split Learning (SL) is a distributed learning framework renowned for its privacy-preserving features and minimal computational requirements. Previous research consistently highligh…
Is Difficulty Calibration All We Need? Towards More Practical Membership Inference Attacks
Yu He, Boheng Li, Yao Wang +4
The vulnerability of machine learning models to Membership Inference Attacks (MIAs) has garnered considerable attention in recent years. These attacks determine whether a data samp…