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20232026
most citedPatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection

6 citations · 8 across the 28 of their papers we have counts for

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7 papers · 1 filter

cs.CR2025

SyncGuard: Robust Audio Watermarking Capable of Countering Desynchronization Attacks

Zhenliang Gan, Xiaoxiao Hu, Sheng Li +2

Audio watermarking has been widely applied in copyright protection and source tracing. However, due to the inherent characteristics of audio signals, watermark localization and res…

cs.CR2025

CoTSRF: Utilize Chain of Thought as Stealthy and Robust Fingerprint of Large Language Models

Zhenzhen Ren, GuoBiao Li, Sheng Li +2

Despite providing superior performance, open-source large language models (LLMs) are vulnerable to abusive usage. To address this issue, recent works propose LLM fingerprinting met…

cs.CR2025

GenPTW: Latent Image Watermarking for Provenance Tracing and Tamper Localization

Zhenliang Gan, Chunya Liu, Yichao Tang +4

The proliferation of generative image models has revolutionized AIGC creation while amplifying concerns over content provenance and manipulation forensics. Existing methods are typ…

cs.CR2024

Revocable Backdoor for Deep Model Trading

Yiran Xu, Nan Zhong, Zhenxing Qian +1

Deep models are being applied in numerous fields and have become a new important digital product. Meanwhile, previous studies have shown that deep models are vulnerable to backdoor…

cs.CR2024

Cover-separable Fixed Neural Network Steganography via Deep Generative Models

Guobiao Li, Sheng Li, Zhenxing Qian +1

Image steganography is the process of hiding secret data in a cover image by subtle perturbation. Recent studies show that it is feasible to use a fixed neural network for data emb…

cs.CR2024

Purified and Unified Steganographic Network

Guobiao Li, Sheng Li, Zicong Luo +2

Steganography is the art of hiding secret data into the cover media for covert communication. In recent years, more and more deep neural network (DNN)-based steganographic schemes…

cs.CR2023

Model Copyright Protection in Buyer-seller Environment

Yusheng Guo, Nan Zhong, Zhenxing Qian +1

Training a deep neural network (DNN) requires a high computational cost. Buying models from sellers with a large number of computing resources has become prevailing. However, the b…