# Combating Fake News with Cryptography in Quantum Era with Post-Quantum Verifiable Image Proofs
## 3 Post-Quantum VerITAS: A zk-SNARK-Based Framework for Secure Image Provenance Verification  
VerITAS represents a groundbreaking approach to ensuring the provenance of edited images by leveraging zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs). Unlike traditional methods that rely on trusted third-party editors to re-sign images after modifications, VerITAS uses zk-SNARKs to cryptographically prove that an image has undergone permissible edits without revealing the original content. This ensures  
Figure 1: Image edition steps. end-to-end security, while eliminating the need to trust external editing tools, addressing a critical limitation of existing frameworks like C2 PA [5]. Post-quantum zero-knowledge proofs, the core technology behind Post-Quantum VerITAS, enable the verification of image provenance without disclosing sensitive information about the original image. This property is particularly valuable in scenarios where privacy and authenticity must coexist, such as in journalism or legal documentation. Prior attempts to apply zk-SNARKs to image provenance, such as PhotoProof and the work by [PERSON] et al., faced significant scalability challenges [6]. These solutions were computationally intensive and too slow to handle high-resolution images, making them impractical for real-world use. VerITAS overcomes these limitations by introducing efficient zk-SNARK proofs that are both compact and fast to verify, even in web browsers. It is the first system capable of handling 30-megapixel images efficiently, marking a significant advancement in the field. In our work, Post-Quantum VerITAS, we transform all these concepts into post-quantum ones. The Post-Quantum VerITAS framework operates through two primary components--the prover (editor) and the verifier (browser or reader). The prover generates a post-quantum zk-SNARK proof that certifies the image has undergone permissible edits, such as cropping, blurring, resizing, or grayscale conversion, while maintaining its authenticity. The verifier, typically implemented in a browser or reader application, checks the proof to confirm the image's provenance without requiring access to the original file or trusting the editing software. This decentralized approach ensures that the integrity of the image is preserved throughout the editing process, even when multiple modifications are applied. One of the key innovations of VerITAS is its ability to handle common editing operations without breaking the image's authenticity. In Post-Quantum VerITAS, we have the same capabilities but are also resistant against attacks by quantum computers. By supporting operations, like cropping, blurring, and resizing, Post-Quantum VerITAS accommodates the practical needs of image editors, while maintaining cryptographic integrity. Additionally, the system's succinct proofs are designed to be lightweight, enabling fast verification with minimal computational overhead. This makes Post-Quantum VerITAS suitable for real-time applications, such as verifying images in web browsers or on mobile devices even in post-quantum epoch. The efficiency and scalability and post-quantum resistance of Post-Quantum VerITAS represent a significant step forward in the field of digital content provenance. To support our claim of efficiency and scalability, we analyzed the computational complexity and conducted benchmark tests using 30-megapixel images (~90 MB). For Mode 1 (computationally limited signer), the proof generation time for a permissible edit (e.g., cropping + grayscale) averaged 42 s, and verification took 0.9 s on a standard desktop CPU (Intel i9-12900K, 64 GB RAM). For Mode 2 (computationally powerful signer with polynomial commitments), proof generation was reduced to 18 s, with the same verification time. The SNARK circuits were compiled using artworks with post-quantum curve parameters, and editing proofs used HyperPlonk. This confirms the system is suitable for real-time and browser-based validation, and scales efficiently even for high-resolution inputs.