mlsanityData to 7 Oct 2026

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

arXiv 2503.11404 ↗First posted 14 Mar 2025cs.CR cs.AI cs.CVcited by 3

On the map: Diffusion models → Robustness, privacy and adversarial aspects

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Robustness, privacy and adversarial aspects, one of 14 directions in Diffusion models. Builds on 8 of its 14 references that are in the map. First posted on arXiv 14 Mar 2025.

Builds on

8 of 14 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models4 Dec
  2. 2024An Undetectable Watermark for Generative Image Models9 Oct
  3. 2024Gaussian Shading: Provable Performance-Lossless Image Watermarking for Diffusion Models7 Apr

Other references · 5

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2019Robust Invisible Video Watermarking with Attentioncited by 144
  4. 2024RingID: Rethinking Tree-Ring Watermarking for Enhanced Multi-Key Identificationcited by 87
  5. 2024Pseudorandom Error-Correcting Codescited by 40

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Gaussian Shannon: High-Precision Diffusion Model Watermarking Based on Communication
  2. 2025SEAL: Semantic Aware Image Watermarking
  3. 2026RAIN: Region-Aware Inversion Network for Semantic Watermark Extraction
  4. 2025SWA-LDM: Toward Stealthy Watermarks for Latent Diffusion Models
  5. 2025Semantic Watermarking Reinvented: Enhancing Robustness and Generation Quality with Fourier Integrity
  6. 2025HMARK: Radioactive Multi-Bit Semantic-Latent Watermarking for Diffusion Models
  7. 2026Correlation-Aware and Gaussianity-Preserving Robust Latent Angular Watermarking for Diffusion Models
  8. 2025PT-Mark: Invisible Watermarking for Text-to-image Diffusion Models via Semantic-aware Pivotal Tuning