mlsanityData to 7 Oct 2026

Authenticated Contradictions from Desynchronized Provenance and Watermarking

arXiv 2603.02378 ↗First posted 2 Mar 2026cs.CR cs.CV cs.MMcited by 2

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Abstract (arXiv)

Cryptographic provenance standards such as C2PA and invisible watermarking are positioned as complementary defenses for content authentication, yet the two verification layers are technically independent: neither conditions on the output of the other. This work formalizes and empirically demonstrates the textitIntegrity Clash, a condition in which a digital asset carries a cryptographically valid C2PA manifest asserting human authorship while its pixels simultaneously carry a watermark identifying it as AI-generated, with both signals passing their respective verification checks in isolation. We construct metadata washing workflows that produce these authenticated fakes through standard editing pipelines, requiring no cryptographic compromise, only the semantic omission of a single assertion field permitted by the current C2PA specification. To close this gap, we propose a cross-layer audit protocol that jointly evaluates provenance metadata and watermark detection status, achieving 100% classification accuracy across 3,500 test images spanning four conflict-matrix states and three realistic perturbation conditions. Our results demonstrate that the gap between these verification layers is unnecessary and technically straightforward to close.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 24 of its 53 references that are in the map. First posted on arXiv 2 Mar 2026.

Builds on

24 of 53 references.

References · 24

  1. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  2. 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,287
  3. 2018HiDDeN: Hiding Data With Deep Networkscited by 384
  4. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 289
  5. 2019StegaStamp: Invisible Hyperlinks in Physical Photographscited by 256
  6. 2023Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robustcited by 179
  7. 2024Gaussian Shading: Provable Performance-Lossless Image Watermarking for Diffusion Modelscited by 131
  8. 2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 124
  9. 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attackscited by 75
  10. 2023Leveraging Optimization for Adaptive Attacks on Image Watermarkscited by 50
  11. 2023GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Modelscited by 40
  12. 2025SynthID-Image: Image watermarking at internet scalecited by 26
12 more
  1. 2024As Good As A Coin Toss: Human detection of AI-generated images, videos, audio, and audiovisual stimulicited by 22
  2. 2024UnMarker: A Universal Attack on Defensive Image Watermarkingcited by 19
  3. 2025Pixel Seal: Adversarial-only training for invisible image and video watermarkingcited by 14
  4. 2025On the Difficulty of Constructing a Robust and Publicly-Detectable Watermarkcited by 9
  5. 2025Watermarking Without Standards Is Not AI Governancecited by 9
  6. 2025Adoption of Watermarking for Generative AI Systems in Practice and Implications under the new EU AI Actcited by 7
  7. 2025First-Place Solution to NeurIPS 2024 Invisible Watermark Removal Challengecited by 7
  8. 2025From Evidence to Verdict: An Agent-Based Forensic Framework for AI-Generated Image Detectioncited by 5
  9. 2024Interoperable Provenance Authentication of Broadcast Media using Open Standards-based Metadata, Watermarking and Cryptographycited by 4
  10. 2020From Attack to Protection: Leveraging Watermarking Attack Network for Advanced Add-on Watermarkingcited by 3
  11. 2026Origin Lens: A Privacy-First Mobile Framework for Cryptographic Image Provenance and AI Detectioncited by 2
  12. 2025Signing Right Awaycited by 1

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Citing papers per year: 2026: 2.

2 papers.