2 citations · 3 across the 30 of their papers we have counts for
11 papers · 1 filter
Cordon-MAS: Defending RAG against Knowledge Poisoning via Information-Flow Control
Zhe Yu, Wenpeng Xing, Gaolei Li +4
Retrieval-augmented generation (RAG) increasingly underpins high-stakes applications, yet remains vulnerable to Confundo-style poisoning where adversarially optimized documents man…
KinGuard: Hierarchical Kinship-Aware Fingerprinting to Defend Against Large Language Model Stealing
Zhenhua Xu, Xiaoning Tian, Wenjun Zeng +5
Protecting the intellectual property of large language models requires robust ownership verification. Conventional backdoor fingerprinting, however, is flawed by a stealth-robustne…
ForgetMark: Stealthy Fingerprint Embedding via Targeted Unlearning in Language Models
Zhenhua Xu, Haobo Zhang, Zhebo Wang +4
Existing invasive (backdoor) fingerprints suffer from high-perplexity triggers that are easily filtered, fixed response patterns exposed by heuristic detectors, and spurious activa…
EverTracer: Hunting Stolen Large Language Models via Stealthy and Robust Probabilistic Fingerprint
Zhenhua Xu, Meng Han, Wenpeng Xing
The proliferation of large language models (LLMs) has intensified concerns over model theft and license violations, necessitating robust and stealthy ownership verification. Existi…
PREE: Towards Harmless and Adaptive Fingerprint Editing in Large Language Models via Knowledge Prefix Enhancement
Xubin Yue, Zhenhua Xu, Wenpeng Xing +3
Addressing the intellectual property protection challenges in commercial deployment of large language models (LLMs), existing black-box fingerprinting techniques face dual challeng…
MCP-Guard: A Multi-Stage Defense-in-Depth Framework for Securing Model Context Protocol in Agentic AI
Wenpeng Xing, Zhonghao Qi, Yupeng Qin +6
While Large Language Models (LLMs) have achieved remarkable performance, they remain vulnerable to jailbreak. The integration of Large Language Models (LLMs) with external tools vi…
MEraser: An Effective Fingerprint Erasure Approach for Large Language Models
Jingxuan Zhang, Zhenhua Xu, Rui Hu +3
Large Language Models (LLMs) have become increasingly prevalent across various sectors, raising critical concerns about model ownership and intellectual property protection. Althou…
SRAF: Stealthy and Robust Adversarial Fingerprint for Copyright Verification of Large Language Models
Zhebo Wang, Zhenhua Xu, Maike Li +5
The protection of Intellectual Property (IP) for Large Language Models (LLMs) has become a critical concern as model theft and unauthorized commercialization escalate. While advers…
Towards Robust and Secure Embodied AI: A Survey on Vulnerabilities and Attacks
Wenpeng Xing, Minghao Li, Mohan Li +1
Embodied AI systems, including robots and autonomous vehicles, are increasingly integrated into real-world applications, where they encounter a range of vulnerabilities stemming fr…
GenTel-Safe: A Unified Benchmark and Shielding Framework for Defending Against Prompt Injection Attacks
Rongchang Li, Minjie Chen, Chang Hu +3
Large Language Models (LLMs) like GPT-4, LLaMA, and Qwen have demonstrated remarkable success across a wide range of applications. However, these models remain inherently vulnerabl…
Fingerprint Vector: Enabling Scalable and Efficient Model Fingerprint Transfer via Vector Addition
Zhenhua Xu, Qichen Liu, Zhebo Wang +4
Backdoor-based fingerprinting has emerged as an effective technique for tracing the ownership of large language models. However, in real-world deployment scenarios, developers ofte…