ZK-JPEG: Zero-knowledge Image Editing and Compression
Cryptographers present ZK-JPEG, a zero-knowledge proof system verifying a published JPEG was correctly compressed from a signed camera image.
IACR ePrint paper 2026/2039 introduces ZK-JPEG, a cryptographic tool from researchers at Stealth Software Technologies and the University of Vermont. It uses zero-knowledge proofs to show a published image derives from a secret committed input while surviving lossy JPEG encoding, which invalidates camera attestation signatures. The system verifies a large family of image transformations, such as blurring and redaction, by integrating them into JPEG compression with minimal cost. It is built with PicoZK, which compiles Python image-editing code into circuits for the line-point zero-knowledge (LPZK) proof system, and is motivated by defending image provenance against deepfakes.
- Proves a published JPEG was correctly compressed from a secret committed input
- Survives lossy JPEG encoding, unlike prior zero-knowledge image-provenance schemes
- Verifies blurring, redaction, and other transformations within the compression process
- Built with PicoZK and the LPZK proof system from off-the-shelf ZK tools
- Motivated by camera attestation to counter deepfake photographs
Full article261 words · extracted from eprint.iacr.org · click to collapse
Paper 2026/2039
ZK-JPEG: Zero-knowledge Image Editing and Compression
Steve Lu
, Stealth Software Technologies, Inc.
Kimberlee Model, Stealth Software Technologies, Inc.
Joseph Near, University of Vermont
Abstract
Tools for generating deep fake photographs are proliferating with greater ease of use and prominence in pop culture. Image authentication tools can defeat these deceitful developments by verifying that a digital image was actually produced by a physical camera. The challenge is that these tools must be robust to desirable image transformations. Camera attestation uses digital signatures to prove an image's provenance from a camera. Lossy compression makes minute changes in order to reduce an image's size, and blurring or redacting regions of an image can protect its subjects. These changes invalidate an image's signature. Prior works use zero-knowledge (ZK) to prove a published image's edit history, but they do not survive lossy encoding such as the JPEG format. We present \zkjpeg, a cryptographic tool for JPEG compression that proves an image was correctly compressed from a secret, committed input. In addition, our tool can verify a large family of image transformations by integrating them into JPEG compression with minimal cost. Our system is fast, flexible, and can be instantiated from off-the-shelf ZK tools. We use PicoZK to convert Python image editing code into a ZK circuit for the line-point zero knowledge (LPZK) proof system.
BibTeX
@misc{cryptoeprint:2026/2039,
author = {Samuel Dittmer and Steve Lu and Kimberlee Model and Joseph Near},
title = {{ZK}-{JPEG}: Zero-knowledge Image Editing and Compression},
howpublished = {Cryptology {ePrint} Archive, Paper 2026/2039},
year = {2026},
url = {https://eprint.iacr.org/2026/2039}
}
Text extracted automatically; images, tables and formatting may be missing. Original: https://eprint.iacr.org/2026/2039