Paper 2026/1914

AIPA: Anonymous Image Provenance Authentication in Online Social Networks via Unlinkable Pseudonym Certificates and zk-SNARKs

Abstract

Generative AI has made high-fidelity deepfakes easy to produce, and online social networks (OSNs) spread them widely across users and platforms. Publicly verifying an image's provenance, i.e., where an image came from and what edits it has undergone, can help combat deepfakes. The Coalition for Content Provenance and Authenticity (C2PA) offers an industry standard, but depends on trusted software and hardware. Through digital signatures and zero-knowledge proofs, cryptographic image authentication eliminates the reliance on trusted editors. However, deploying such schemes in OSNs faces three problems: preserving signer privacy, maintaining provenance authenticity across edits, and ensuring efficient verification. To ensure signer anonymity in image provenance, we propose an unlinkable pseudonym certificate scheme (UPCS) based on anonymous credentials, which reduces online signing and verification to ordinary digital signature operations taking only 0.017 and 0.066 ms. Building on UPCS, zk-SNARKs, and hash chains, we propose an anonymous image provenance authentication (AIPA) scheme, ensuring the authenticity of provenance and editing history of an image as it propagates across mutually untrusted editors, while preserving signer privacy. To achieve efficient verification in OSNs, we introduce VIMz-Loua, a GPU-accelerated image proof system with a dedicated JPEG-compression circuit, whose proofs remain a constant 448 B and verify in 6-12 ms across image sizes. We formally prove the security of UPCS and AIPA, and implement an end-to-end workflow in a simulated OSN environment, where the full multi-edit provenance lineage is only 40.2 KB (6.5% of the published image), and is verified in 4.28 s.