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S&P2025顶会

VerITAS: Verifying Image Transformations at Scale

Trisha Datta, Binyi Chen, Dan Boneh

2025年份
5顶会引用

摘要

Verifying image provenance has become an important topic, especially in the realm of news media. To address this issue, the Coalition for Content Provenance and Authenticity (C2PA) developed a standard to verify image provenance that relies on digital signatures produced by cameras. However, photos are usually edited before being published, and a signature on an original photo cannot be verified given only the published edited image. In this work, we describe VerITAS, a system that uses zero-knowledge proofs (zk-SNARKs) to prove that only certain edits have been applied to a signed photo. While past work has created image editing proofs for photos, VerITAS is the first to do so for realistically large images (30 megapixels). Our key innovation enabling this leap is the design of a new proof system that enables proving knowledge of a valid signature on a large amount of witness data. We run experiments on realistically large images that are more than an order of magnitude larger than those tested in prior work. In the case of a computationally weak signer, such as a camera, we are able to generate a proof of valid edits for a 90 MB image in just over thirteen minutes, costing about 0.54onAWSperimage.Inthecaseofamorepowerfulsigner,weareabletogenerateaproofofvalideditsfora90MBimageinjustoverthreeminutes,costingonly0.54 on AWS per image. In the case of a more powerful signer, we are able to generate a proof of valid edits for a 90 MB image in just over three minutes, costing only 0.13 on AWS per image. Either way, proof verification time is less than a second. Our techniques apply broadly whenever there is a need to prove that an efficient transformation was applied correctly to a large amount of signed private data.

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