用零知识证明隐藏图像出处敏感信息，保护隐私同时保留可信度。
Soft Redaction of Image Provenance via Zero-Knowledge Proofs
- 用零知识证明替代敏感出处信息，隐藏数据但验证性质
- 支持位置、生物特征距离和视觉指纹的隐私化证明，验证仅需毫秒
- 可兼容C2PA标准，适用于版权保护与防伪造场景
内容出处标准（如C2PA）正被广泛用于为数字图像附加来源、编辑历史和权利信息。然而，出处透明性可能与隐私冲突——增强信任的声明也可能暴露创作者或拍摄环境的敏感信息。本文提出图像出处的软去敏机制：将敏感出处断言替换为对隐藏数据的特定属性的零知识证明（ZKP）。研究聚焦于距离证明：首先展示如何通过切比雪夫多项式近似，在ZKP电路中实现对公共参考点的接近性证明；进而扩展至生物特征嵌入的L2距离证明，支持基于相似性的隐私保护主张，以维护肖像权；最后将同一构造应用于感知哈希（视觉指纹），支持水印恢复中剥离出处元数据的反欺骗应用。结果表明，图像出处上的ZKP可实现实用的软去敏功能，兼容C2PA标准，构建仅需数秒，验证耗时毫秒级。
原文摘要 · Abstract (English)
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.
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