7 citations · 15 across the 18 of their papers we have counts for
8 papers · 1 filter
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…
Membership Inference Attacks on Tokenizers of Large Language Models
Meng Tong, Yuntao Du, Kejiang Chen +2
Membership inference attacks (MIAs) are widely used to assess the privacy risks associated with machine learning models. However, when these attacks are applied to pre-trained larg…
De-AntiFake: Rethinking the Protective Perturbations Against Voice Cloning Attacks
Wei Fan, Kejiang Chen, Chang Liu +2
The rapid advancement of speech generation models has heightened privacy and security concerns related to voice cloning (VC). Recent studies have investigated disrupting unauthoriz…
AEDR: Training-Free AI-Generated Image Attribution via Autoencoder Double-Reconstruction
Chao Wang, Zijin Yang, Yaofei Wang +2
The rapid advancement of image-generation technologies has made it possible for anyone to create photorealistic images using generative models, raising significant security concern…
Gaussian Shading++: Rethinking the Realistic Deployment Challenge of Performance-Lossless Image Watermark for Diffusion Models
Zijin Yang, Xin Zhang, Kejiang Chen +5
Ethical concerns surrounding copyright protection and inappropriate content generation pose challenges for the practical implementation of diffusion models. One effective solution…
Provably Secure Public-Key Steganography Based on Admissible Encoding
Xin Zhang, Kejiang Chen, Na Zhao +2
The technique of hiding secret messages within seemingly harmless covertext to evade examination by censors with rigorous security proofs is known as provably secure steganography…
GIFDL: Generated Image Fluctuation Distortion Learning for Enhancing Steganographic Security
Xiangkun Wang, Kejiang Chen, Yuang Qi +3
Minimum distortion steganography is currently the mainstream method for modification-based steganography. A key issue in this method is how to define steganographic distortion. Wit…
SparSamp: Efficient Provably Secure Steganography Based on Sparse Sampling
Yaofei Wang, Gang Pei, Kejiang Chen +5
Steganography embeds confidential data within seemingly innocuous communications. Provable security in steganography, a long-sought goal, has become feasible with deep generative m…