Soft Redaction of Image Provenance via Zero-Knowledge Proofs

2026-08-07

AI Summary

This work addresses the privacy risks inherent in image provenance standards such as C2PA, which, while enhancing content authenticity, may inadvertently disclose sensitive information like creator identity or capture environment. To reconcile transparency with privacy, the paper introduces a “soft sanitization” mechanism that, for the first time, integrates zero-knowledge proofs into image provenance systems. This approach enables selective disclosure by proving only specific properties of redacted metadata—such as geographic proximity, biometric similarity, or perceptual hash distance—without revealing the underlying data. Leveraging an efficient proof circuit based on Chebyshev polynomial approximation, the system supports verification of L∞/L2 distances and perceptual hash similarity. Fully compatible with C2PA, the scheme generates proofs in seconds and verifies them in milliseconds, demonstrating practical feasibility for real-world deployment.

Abstract

Content provenance standards, such as C2PA, are increasingly used to attach signed records of origin, editing history, and rights to digital images. However, provenance transparency can conflict with privacy -- assertions that strengthen trust in an image may also reveal sensitive information about the creator or capture context. We propose soft redaction for image provenance: a mechanism that replaces sensitive provenance assertions with zero-knowledge proofs (ZKPs) of selected properties over hidden data. Our work focuses on distance proofs. We first show how location assertions can support proofs of proximity to a public reference point, using Chebyshev polynomial approximations within the ZKP proof circuit. We then extend the approach to L2 distance proofs over biometric embeddings, enabling privacy-preserving claims related to likeness to help enforce personality rights with images. Finally, we apply the same distance-proof construction to perceptual hashes (visual fingerprints), supporting an anti-spoofing use case in watermark-based recovery of stripped provenance metadata. Our results demonstrate that ZKPs over image provenance can provide practical soft-redaction capabilities, compatible with C2PA, that may be constructed in seconds and verified in milliseconds.

Problem

• image provenance
• privacy
• zero-knowledge proofs
• soft redaction
• sensitive information

Innovation

• zero-knowledge proofs
• soft redaction
• image provenance
• distance proofs
• privacy-preserving