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20202026
most citedReversible Watermarking in Deep Convolutional Neural Networks for Integrity Authentication

45 citations · 113 across the 28 of their papers we have counts for

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Showing cs.CRShow all

11 papers · 1 filter

cs.CR2025

EditMark: Watermarking Large Language Models based on Model Editing

Shuai Li, Kejiang Chen, Jun Jiang +5

Large Language Models (LLMs) have demonstrated remarkable capabilities, but their training requires extensive data and computational resources, rendering them valuable digital asse…

cs.CR2025

SafeGuider: Robust and Practical Content Safety Control for Text-to-Image Models

Peigui Qi, Kunsheng Tang, Wenbo Zhou +5

Text-to-image models have shown remarkable capabilities in generating high-quality images from natural language descriptions. However, these models are highly vulnerable to adversa…

cs.CR2024

On the Vulnerability of Text Sanitization

Meng Tong, Kejiang Chen, Xiaojian Yuan +4

Text sanitization, which employs differential privacy to replace sensitive tokens with new ones, represents a significant technique for privacy protection. Typically, its performan…

cs.CR2024★ 1 cited

AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA

Weitao Feng, Wenbo Zhou, Jiyan He +6

Diffusion models have achieved remarkable success in generating high-quality images. Recently, the open-source models represented by Stable Diffusion (SD) are thriving and are acce…

cs.CR2024

Model X-ray:Detecting Backdoored Models via Decision Boundary

Yanghao Su, Jie Zhang, Ting Xu +3

Backdoor attacks pose a significant security vulnerability for deep neural networks (DNNs), enabling them to operate normally on clean inputs but manipulate predictions when specif…

cs.CR2023

Turning Your Strength into Watermark: Watermarking Large Language Model via Knowledge Injection

Shuai Li, Kejiang Chen, Kunsheng Tang +4

Large language models (LLMs) have demonstrated outstanding performance, making them valuable digital assets with significant commercial potential. Unfortunately, the LLM and its AP…

cs.CR2023

Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World

Zhiling Zhang, Jie Zhang, Kui Zhang +3

The widespread use of face recognition technology has given rise to privacy concerns, as many individuals are worried about the collection and utilization of their facial data. To…

cs.CR2023★ 2 cited

InferDPT: Privacy-Preserving Inference for Closed-box Large Language Model

Meng Tong, Kejiang Chen, Jie Zhang +5

Large language models (LLMs), like ChatGPT, have greatly simplified text generation tasks. However, they have also raised concerns about privacy risks such as data leakage and unau…

cs.CR2023★ 3 cited

Catch You Everything Everywhere: Guarding Textual Inversion via Concept Watermarking

Weitao Feng, Jiyan He, Jie Zhang +4

AIGC (AI-Generated Content) has achieved tremendous success in many applications such as text-to-image tasks, where the model can generate high-quality images with diverse prompts,…

cs.CR2021

Tracing Text Provenance via Context-Aware Lexical Substitution

Xi Yang, Jie Zhang, Kejiang Chen +4

Text content created by humans or language models is often stolen or misused by adversaries. Tracing text provenance can help claim the ownership of text content or identify the ma…

cs.CR2021★ 45 cited

Reversible Watermarking in Deep Convolutional Neural Networks for Integrity Authentication

Xiquan Guan, Huamin Feng, Weiming Zhang +3

Deep convolutional neural networks have made outstanding contributions in many fields such as computer vision in the past few years and many researchers published well-trained netw…