On the Difficulty of Constructing a Robust and Publicly-Detectable Watermark
Fairoze, Jaiden, Ortiz-Jiménez, Guillermo, Vecerik, Mel, Jha, Somesh, Gowal, Sven
–arXiv.org Artificial Intelligence
This work investigates the theoretical boundaries of creating publicly-detectable schemes to enable the provenance of watermarked imagery. Metadata-based approaches like C2PA provide unforgeability and public-detectability. ML techniques offer robust retrieval and watermarking. However, no existing scheme combines robustness, unforgeability, and public-detectability. In this work, we formally define such a scheme and establish its existence. Although theoretically possible, we find that at present, it is intractable to build certain components of our scheme without a leap in deep learning capabilities. We analyze these limitations and propose research directions that need to be addressed before we can practically realize robust and publicly-verifiable provenance.
arXiv.org Artificial Intelligence
Feb-7-2025
- Country:
- North America > United States
- California (0.14)
- Wisconsin (0.14)
- North America > United States
- Genre:
- Research Report (0.64)
- Industry:
- Information Technology > Security & Privacy (1.00)
- Technology: