Stable Signature is Unstable: Removing Image Watermark from Diffusion Models

Yuepeng Hu, Zhengyuan Jiang, Moyang Guo, Neil Gong
5/12/2024
cs.CRcs.CV

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Abstract

Watermark has been widely deployed by industry to detect AI-generated images. A recent watermarking framework called \emph{Stable Signature} (proposed by Meta) roots watermark into the parameters of a diffusion model's decoder such that its generated images are inherently watermarked. Stable Signature makes it possible to watermark images generated by \emph{open-source} diffusion models and was claimed to be robust against removal attacks. In this work, we propose a new attack to remove the watermark from a diffusion model by fine-tuning it. Our results show that our attack can effectively remove the watermark from a diffusion model such that its generated images are non-watermarked, while maintaining the visual quality of the generated images. Our results highlight that Stable Signature is not as stable as previously thought.

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Cite this paper

@article{hu2024stable,
  title  = {Stable Signature is Unstable: Removing Image Watermark from Diffusion Models},
  author = {Yuepeng Hu and Zhengyuan Jiang and Moyang Guo and Neil Gong},
  year   = {2024},
  eprint = {2405.07145},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2405.07145v1}
}

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