activity
20232026
most citedAdversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples

19 citations · 37 across the 14 of their papers we have counts for

collaborators
Showing cs.CRShow all

8 papers · 1 filter

cs.CR2026

Inhibitory Attacks on Backdoor-based Fingerprinting for Large Language Models

Hang Fu, Wanli Peng, Yinghan Zhou +3

The widespread adoption of Large Language Model (LLM) in commercial and research settings has intensified the need for robust intellectual property protection. Backdoor-based LLM f…

cs.CR2025

Self-Disguise Attack: Induce the LLM to disguise itself for AIGT detection evasion

Yinghan Zhou, Juan Wen, Wanli Peng +3

AI-generated text (AIGT) detection evasion aims to reduce the detection probability of AIGT, helping to identify weaknesses in detectors and enhance their effectiveness and reliabi…

cs.CR2025

EditMF: Drawing an Invisible Fingerprint for Your Large Language Models

Jiaxuan Wu, Yinghan Zhou, Wanli Peng +3

Training large language models (LLMs) is resource-intensive and expensive, making protecting intellectual property (IP) for LLMs crucial. Recently, embedding fingerprints into LLMs…

cs.CR2025

SLIP: Soft Label Mechanism and Key-Extraction-Guided CoT-based Defense Against Instruction Backdoor in APIs

Zhengxian Wu, Juan Wen, Wanli Peng +3

Customized Large Language Model (LLM) agents face a critical security threat from black-box instruction backdoors, where malicious behaviors are covertly injected through hidden sy…

cs.CR2025

BeDKD: Backdoor Defense Based on Directional Mapping Module and Adversarial Knowledge Distillation

Zhengxian Wu, Juan Wen, Wanli Peng +3

Although existing backdoor defenses have gained success in mitigating backdoor attacks, they still face substantial challenges. In particular, most of them rely on large amounts of…

cs.CR2025

Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models

Wanli Peng, Xin Chen, Hang Fu +3

Recent advances in large language models (LLMs) have made a profound impact on our society and also raised new security concerns. Particularly, due to the remarkable inference abil…

cs.CR2025

GTSD: Generative Text Steganography Based on Diffusion Model

Zhengxian Wu, Juan Wen, Yiming Xue +2

With the rapid development of deep learning, existing generative text steganography methods based on autoregressive models have achieved success. However, these autoregressive steg…

cs.CR2025

Protecting Creative Writing Copyright against AI Imitation via Implicit Watermarking

Ziwei Zhang, Juan Wen, Wanli Peng +3

Large language models (LLMs) enable powerful knowledge injection through approaches such as in-context learning and fine-tuning, but they also introduce new risks of unauthorized i…