Paper 2024/1063

VIMz: Private Proofs of Image Manipulation using Folding-based zkSNARKs

Stefan Dziembowski, University of Warsaw, IDEAS NCBR
Shahriar Ebrahimi, IDEAS NCBR
Parisa Hassanizadeh, Polish Academy of Sciences, IDEAS NCBR
Abstract

Ensuring the authenticity and credibility of daily media on internet is an ongoing problem. Meanwhile, genuinely captured images often require refinements before publication. Zero-knowledge proofs (ZKPs) offer a solution by verifying edited image without disclosing the original source. However, ZKPs typically come with high costs, particularly in terms of prover complexity and proof size. This paper presents VIMz, a framework for efficiently proving the authenticity of high-resolution images using folding-based zkSNARKs; a type of proving system that minimizes computational overhead by recursively folding multiple evaluations of the same constraints into a compact proof. As a complete proof system, VIMz proves the integrity of both the original and edited images, as well as the correctness of the transformation without revealing intermediate images within a chain of edits--only the final result is disclosed. Moreover, VIMz maintains the anonymity of the original signer and all subsequent editors while proving the authenticity of the final image. We also compare VIMz with the system model in Coalition for Content Provenance and Authenticity (C2PA) from different perspectives and show that VIMz offers higher level of security guarantee by eliminating the need to trust the editing environment. Experimental results show that VIMz performs efficiently in both prover and verifier sides. It can prove the transformations on 8K (33MP,i.e., 100MB) images with up to 13%~25% faster than the competition, while reaching to a peak memory of only 10 GB. Moreover, VIMz has a verification time of under 1 second and achieves succinct proofs of less than 11 KB for all resolutions, which is more than 90% improvement compared to the competition. VIMz’s low memory complexity allows for proving multiple transformations in parallel to achieve a 3.5x additional speedup on average.

Note: PETS 2025 Camera-ready version. Added detailed comparison with cuncurrent work. Added benchmarks for 8K (33MP) resolution. Added unconditional (independent from infrastructure) privacy-preserving version. Updated the Artifacts Appendix.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Published elsewhere. Minor revision. The 25th Privacy Enhancing Technologies Symposium (PETS)
Keywords
Folding SchemezkSNARKsZero-knowledge proofsMedia AuthenticityDisinformationFake NewsProof of ProvenanceC2PA
Contact author(s)
Stefan Dziembowski @ crypto edu pl
shahriar ebrahimi @ ideas-ncbr pl
parisa hassanizadeh @ ideas-ncbr pl
History
2024-12-11: last of 3 revisions
2024-06-29: received
See all versions
Short URL
https://ia.cr/2024/1063
License
Creative Commons Attribution-NonCommercial
CC BY-NC

BibTeX

@misc{cryptoeprint:2024/1063,
      author = {Stefan Dziembowski and Shahriar Ebrahimi and Parisa Hassanizadeh},
      title = {{VIMz}: Private Proofs of Image Manipulation using Folding-based {zkSNARKs}},
      howpublished = {Cryptology {ePrint} Archive, Paper 2024/1063},
      year = {2024},
      url = {https://eprint.iacr.org/2024/1063}
}
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