15 citations · 22 across the 6 of their papers we have counts for
6 papers
Caliber: Cross-Architecture Extraction-Cost Control for Score-Returning APIs
Chi Wang, Hanwen Wang, Yu Xia +2
We present Caliber, an output-perturbation defense against model extraction that formulates noise selection as a calibration problem: how much the defense degrades the supervision…
AI Model Modulation with Logits Redistribution
Zihan Wang, Zhongkui Ma, Xinguo Feng +5
Large-scale models are typically adapted to meet the diverse requirements of model owners and users. However, maintaining multiple specialized versions of the model is inefficient.…
Re-Key-Free, Risky-Free: Adaptable Model Usage Control
Zihan Wang, Zhongkui Ma, Xinguo Feng +6
Deep neural networks (DNNs) have become valuable intellectual property of model owners, due to the substantial resources required for their development. To protect these assets in…
Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization
Zihan Wang, Zhiyong Ma, Zhongkui Ma +5
Recent AI regulations increasingly emphasize the need for mechanisms that preserve the utility of data for AI innovation while preventing misuse, particularly by enforcing purpose…
Uncovering Gradient Inversion Risks in Practical Language Model Training
Xinguo Feng, Zhongkui Ma, Zihan Wang +4
The gradient inversion attack has been demonstrated as a significant privacy threat to federated learning (FL), particularly in continuous domains such as vision models. In contras…
Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography
Zihan Wang, Olivia Byrnes, Hu Wang +5
The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding. By embedding infor…