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20242026
most citedA Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures

2 citations · 2 across the 10 of their papers we have counts for

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cs.CR2026

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…

cs.CR2025

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends

Zhenhua Xu, Xubin Yue, Zhebo Wang +9

Copyright protection for large language models is of critical importance, given their substantial development costs, proprietary value, and potential for misuse. Existing surveys h…

cs.CR2025★ 2 cited

A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures

Dezhang Kong, Shi Lin, Zhenhua Xu +16

In recent years, Large-Language-Model-driven AI agents have exhibited unprecedented intelligence and adaptability. Nowadays, agents are undergoing a new round of evolution. They no…

cs.CR2025

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…

cs.CR2024

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…