2025/02/07 by Jaiden Fairoze, Guillermo Ortiz-Jimenez, Guillermo Ortiz-Jiménez +9 · 1 voice · 3 citations
Computer Science · #Advanced Steganography and Watermarking Techniques #Chaos-based Image/Signal Encryption #Cryptography and Data Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.CR #cs.LG
paper · pdf · doi:10.48550/arxiv.2502.04901
openalex publication_date 2025/02/07 · arxiv published 2025/02/07 · arxiv updated 2025/04/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.