3 citations · 3 across the 11 of their papers we have counts for
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Learning to Watermark Speech Synthesis Against Model-Driven Reconstruction
Weizhi Liu, Yue Li, Hui Tian +1
Modern TTS systems increasingly generate synthetic speech at scale for diverse users. This setting calls for content-level provenance that can verify the origin of released speech…
TI-StegoAlign: Channel-Guided Post-Training for Generative Text Steganography under Tokenization Inconsistency
Jiuan Zhou, Yuhao Xue, Yu Cheng +2
Generative text steganography enables LLM agents to exchange secret information through task-relevant messages. Yet most methods evaluate recovery on sender-side tokens, whereas th…
Benign in Isolation, Harmful in Composition: Security Risks in Agent Skill Ecosystems
Yi Xie, Jiawei Du, Yu Cheng +2
Skills are becoming the capability layer through which LLM agents turn plans into actions, but their use introduces security risks such as data leakage, unauthorized operations, an…
DTAMS: High-Capacity Generative Steganography via Dynamic Multi-Timestep Selection and Adaptive Deviation Mapping in Latent Diffusion
Yuhao Xue, Jiuan Zhou, Yu Cheng +1
With the rapid development of AIGC technologies, generative image steganography has attracted increasing attention due to its high imperceptibility and flexibility. However, existi…
VocBulwark: Towards Practical Generative Speech Watermarking via Additional-Parameter Injection
Weizhi Liu, Yue Li, Zhaoxia Yin
Generated speech achieves human-level naturalness but escalates security risks of misuse. However, existing watermarking methods fail to reconcile fidelity with robustness, as they…
Robust Reversible Watermarking in Encrypted Images Based on Dual-MSBs Spiral Embedding
Haoyu Shen, Wen Yin, Zhaoxia Yin +2
Robust reversible watermarking in encrypted images (RRWEI) faces an inherent challenge in simultaneously achieving robustness, reversibility, and content privacy under severely con…
Auto-Stega: An Agent-Driven System for Lifelong Strategy Evolution in LLM-Based Text Steganography
Jiuan Zhou, Yu Cheng, Yuan Xie +1
With the rapid progress of LLMs, high quality generative text has become widely available as a cover for text steganography. However, prevailing methods rely on hand-crafted or pre…
Robust Steganography with Boundary-Preserving Overflow Alleviation and Adaptive Error Correction
Yu Cheng, Zhenlin Luo, Zhaoxia Yin
With the rapid evolution of the Internet, the vast amount of data has created opportunities for fostering the development of steganographic techniques. However, traditional stegano…
A Survey of Fragile Model Watermarking
Zhenzhe Gao, Yu Cheng, Zhaoxia Yin
Model fragile watermarking, inspired by both the field of adversarial attacks on neural networks and traditional multimedia fragile watermarking, has gradually emerged as a potent…
Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing
ZhenZhe Gao, Zhenjun Tang, Zhaoxia Yin +2
Neural networks have increasingly influenced people's lives. Ensuring the faithful deployment of neural networks as designed by their model owners is crucial, as they may be suscep…