AI-Enhanced Perceptual Hashing with Blockchain for Secure and Transparent Digital Copyright Management

Meng, Zhaoxiong; Zhang, Rukui; Cao, Bin; Zhang, Meng; Li, Yajun; Xue, Huhu; Yang, Meimei

doi:10.3390/cryptography10010002

Open AccessArticle

AI-Enhanced Perceptual Hashing with Blockchain for Secure and Transparent Digital Copyright Management

by

Zhaoxiong Meng

^*

,

Rukui Zhang

,

Bin Cao

,

Meng Zhang

,

Yajun Li

,

Huhu Xue

and

Meimei Yang

Faculty of Electronic Information and Electrical Engineering, Tianshui Normal University, Tianshui 741000, China

^*

Author to whom correspondence should be addressed.

Cryptography 2026, 10(1), 2; https://doi.org/10.3390/cryptography10010002

Submission received: 10 November 2025 / Revised: 28 November 2025 / Accepted: 25 December 2025 / Published: 29 December 2025

(This article belongs to the Special Issue Interdisciplinary Cryptography)

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Abstract

This study presents a novel framework for digital copyright management that integrates AI-enhanced perceptual hashing, blockchain technology, and digital watermarking to address critical challenges in content protection and verification. Traditional watermarking approaches typically employ content-independent metadata and rely on centralized authorities, introducing risks of tampering and operational inefficiencies. The proposed system utilizes a pre-trained convolutional neural network (CNN) to generate a robust, content-based perceptual hash value, which serves as an unforgeable watermark intrinsically linked to the image content. This hash is embedded as a QR code in the frequency domain and registered on a blockchain, ensuring tamper-proof timestamping and comprehensive traceability. The blockchain infrastructure further enables verification of multiple watermark sequences, thereby clarifying authorship attribution and modification history. Experimental results demonstrate high robustness against common image modifications, strong discriminative capabilities, and effective watermark recovery, supported by decentralized storage via the InterPlanetary File System (IPFS). The framework provides a transparent, secure, and efficient solution for digital rights management, with potential future enhancements including post-quantum cryptography integration.

Keywords: AI-assisted cryptography; perceptual hashing; convolutional neural network (CNN); blockchain; digital watermarking; copyright management

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MDPI and ACS Style

Meng, Z.; Zhang, R.; Cao, B.; Zhang, M.; Li, Y.; Xue, H.; Yang, M. AI-Enhanced Perceptual Hashing with Blockchain for Secure and Transparent Digital Copyright Management. Cryptography 2026, 10, 2. https://doi.org/10.3390/cryptography10010002

AMA Style

Meng Z, Zhang R, Cao B, Zhang M, Li Y, Xue H, Yang M. AI-Enhanced Perceptual Hashing with Blockchain for Secure and Transparent Digital Copyright Management. Cryptography. 2026; 10(1):2. https://doi.org/10.3390/cryptography10010002

Chicago/Turabian Style

Meng, Zhaoxiong, Rukui Zhang, Bin Cao, Meng Zhang, Yajun Li, Huhu Xue, and Meimei Yang. 2026. "AI-Enhanced Perceptual Hashing with Blockchain for Secure and Transparent Digital Copyright Management" Cryptography 10, no. 1: 2. https://doi.org/10.3390/cryptography10010002

APA Style

Meng, Z., Zhang, R., Cao, B., Zhang, M., Li, Y., Xue, H., & Yang, M. (2026). AI-Enhanced Perceptual Hashing with Blockchain for Secure and Transparent Digital Copyright Management. Cryptography, 10(1), 2. https://doi.org/10.3390/cryptography10010002

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AI-Enhanced Perceptual Hashing with Blockchain for Secure and Transparent Digital Copyright Management

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