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Stable Signature is Unstable: Removing Image Watermark from Diffusion Models
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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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Watermarking across Modalities for Content Tracing and Generative AI
A thesis showing that invisible watermarks can be embedded across images, audio, text, and model weights, with statistical tests for tracing AI-generated content.
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