Edited Image Verification With Tiled Hashes and Zero-Knowledge Proofs
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Solution Overview
Problem
Existing image verification technologies, such as PhotoProof, face inefficiencies in execution time due to lengthy mathematical calculations when verifying image edits, and fail to distinguish between malicious and authorized modifications, compromising privacy protection.
Innovation Solution
A system comprising a producer, editor, and user terminal device, utilizing tiling and zero-knowledge proof (ZKP) technology to verify edited images by generating and comparing hash values, ensuring only the operator of the producer and editor can view the original content, thus protecting privacy while reducing computation time and storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If PhotoProof technology is used to verify image editing authorization, then privacy protection is improved, but execution time increases due to lengthy mathematical calculations
Solution Approach 1:
The patent divides the image into multiple tiles and processes each tile independently. Instead of performing cryptographic operations on the entire image, the system segments the verification process into smaller units (tiles), allowing parallel processing and reducing overall execution time while maintaining privacy protection through selective tile editing verification.
Solution Approach 2:
The patent implements partial verification by only processing tiles that were edited rather than the entire image. The system identifies which tiles contain edits and performs verification only on those specific tiles, reducing the computational burden from processing the full image to processing only the modified portions.
2Reliability
If entire image encryption is applied to protect privacy, then privacy protection is improved, but computation time increases
Solution Approach 1:
The patent extracts only the necessary portions (edited tiles) from the entire image for verification. Instead of encrypting and processing the complete image, the system identifies and extracts only the tiles that require verification, separating the verification process from the rest of the image data to improve efficiency.
Solution Approach 2:
The patent applies different processing qualities to different parts of the image. Edited tiles receive full cryptographic verification while non-edited tiles are excluded from processing. This local quality approach ensures privacy protection is applied only where necessary (edited regions) rather than uniformly across the entire image.
3Measurement precision
If full image verification is performed, then verification accuracy is improved, but storage requirements increase
Solution Approach 1:
The patent segments the image verification process into individual tile verifications. Each tile is verified independently and stored separately, allowing the system to maintain verification accuracy for each tile while reducing overall storage requirements by only storing verification data for edited tiles rather than the entire image.
Data Source
AI summary
A system for verifying edited image includes: a producer terminal device configured to tile a source image for a plurality of smaller tiled images with individual source image hash values to accordingly calculate an integrated source image hash value, and to execute digitally signing to generate an image tag pair; an editor terminal device configured to receive the image tag pair, to divide the source image into these smaller tiled images according to a tile configuration, to edit part of the smaller tiled images, to include the rest part of these smaller tiled images to generate an edited integral image and further calculate an integrated edit image hash value, and to execute digitally signing to generate a zero-knowledge proof (ZKP) assurance; and, a user terminal device configured to receive the ZKP assurance to accordingly verify whether or not the edited integral image is generated by editing the source image.