8 citations · 25 across the 24 of their papers we have counts for
8 papers · 1 filter
LiteUpdate: A Lightweight Framework for Updating AI-Generated Image Detectors
Jiajie Lu, Zhenkan Fu, Na Zhao +4
The rapid progress of generative AI has led to the emergence of new generative models, while existing detection methods struggle to keep pace, resulting in significant degradation…
A high-capacity linguistic steganography based on entropy-driven rank-token mapping
Jun Jiang, Weiming Zhang, Nenghai Yu +1
Linguistic steganography enables covert communication through embedding secret messages into innocuous texts; however, current methods face critical limitations in payload capacity…
T2SMark: Balancing Robustness and Diversity in Noise-as-Watermark for Diffusion Models
Jindong Yang, Han Fang, Weiming Zhang +2
Diffusion models have advanced rapidly in recent years, producing high-fidelity images while raising concerns about intellectual property protection and the misuse of generative AI…
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…