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Towards A Correct Usage of Cryptography in Semantic Watermarks for Diffusion Models

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arxiv 2503.11404 v1 pith:LQYVNY6L submitted 2025-03-14 cs.CR cs.AIcs.CV

classification cs.CRcs.AIcs.CV
keywords semanticcryptographicwatermarkslatentprimitivesdiffusiongaussiangeneration
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abstract

Semantic watermarking methods enable the direct integration of watermarks into the generation process of latent diffusion models by only modifying the initial latent noise. One line of approaches building on Gaussian Shading relies on cryptographic primitives to steer the sampling process of the latent noise. However, we identify several issues in the usage of cryptographic techniques in Gaussian Shading, particularly in its proof of lossless performance and key management, causing ambiguity in follow-up works, too. In this work, we therefore revisit the cryptographic primitives for semantic watermarking. We introduce a novel, general proof of lossless performance based on IND\$-CPA security for semantic watermarks. We then discuss the configuration of the cryptographic primitives in semantic watermarks with respect to security, efficiency, and generation quality.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models

    cs.CR 2024-12 conditional novelty 7.0 of 10

    Using a proxy diffusion model and a single watermarked reference image, an attacker can imprint or erase Tree-Ring and Gaussian Shading watermarks on arbitrary images.

  2. Gaussian Shading++: Rethinking the Realistic Deployment Challenge of Performance-Lossless Image Watermark for Diffusion Models

    cs.CV 2025-04 conditional novelty 6.0 of 10

    Gaussian Shading++ hides an invisible watermark in diffusion images using a fixed key, storing the random seed in a pseudorandom error-correcting header and improving extraction with soft-decision decoding.

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