[PDF][PDF] An overview of compressible and learnable image transformation with secret key and its applications

H Kiya, APM Maung, Y Kinoshita… - … on Signal and …, 2022 - nowpublishers.com
This article presents an overview of image transformation with a secret key and its
applications. Image transformation with a secret key enables us not only to protect visual …

A systematic review on model watermarking for neural networks

F Boenisch - Frontiers in big Data, 2021 - frontiersin.org
Machine learning (ML) models are applied in an increasing variety of domains. The
availability of large amounts of data and computational resources encourages the …

A recipe for watermarking diffusion models

Y Zhao, T Pang, C Du, X Yang, NM Cheung… - arxiv preprint arxiv …, 2023 - arxiv.org
Diffusion models (DMs) have demonstrated advantageous potential on generative tasks.
Widespread interest exists in incorporating DMs into downstream applications, such as …

{REMARK-LLM}: A robust and efficient watermarking framework for generative large language models

R Zhang, SS Hussain, P Neekhara… - 33rd USENIX Security …, 2024 - usenix.org
We present REMARK-LLM, a novel efficient, and robust watermarking framework designed
for texts generated by large language models (LLMs). Synthesizing human-like content …

Artificial fingerprinting for generative models: Rooting deepfake attribution in training data

N Yu, V Skripniuk, S Abdelnabi… - Proceedings of the …, 2021 - openaccess.thecvf.com
Photorealistic image generation has reached a new level of quality due to the breakthroughs
of generative adversarial networks (GANs). Yet, the dark side of such deepfakes, the …

A survey of deep neural network watermarking techniques

Y Li, H Wang, M Barni - Neurocomputing, 2021 - Elsevier
Abstract Protecting the Intellectual Property Rights (IPR) associated to Deep Neural
Networks (DNNs) is a pressing need pushed by the high costs required to train such …

Protecting intellectual property of large language model-based code generation apis via watermarks

Z Li, C Wang, S Wang, C Gao - Proceedings of the 2023 ACM SIGSAC …, 2023 - dl.acm.org
The rise of large language model-based code generation (LLCG) has enabled various
commercial services and APIs. Training LLCG models is often expensive and time …

Adversarial watermarking transformer: Towards tracing text provenance with data hiding

S Abdelnabi, M Fritz - 2021 IEEE Symposium on Security and …, 2021 - ieeexplore.ieee.org
Recent advances in natural language generation have introduced powerful language
models with high-quality output text. However, this raises concerns about the potential …

Robust watermarking for deep neural networks via bi-level optimization

P Yang, Y Lao, P Li - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
Deep neural networks (DNNs) have become state-of-the-art in many application domains.
The increasing complexity and cost for building these models demand means for protecting …

Responsible disclosure of generative models using scalable fingerprinting

N Yu, V Skripniuk, D Chen, L Davis, M Fritz - arxiv preprint arxiv …, 2020 - arxiv.org
Over the past years, deep generative models have achieved a new level of performance.
Generated data has become difficult, if not impossible, to be distinguished from real data …