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Digital image copyright protection method based on blockchain and zero trust mechanism

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Abstract

In order to make the image copyright protection system can resist network attacks, and to solve the problems of unknown copyright owner, difficulty in data integrity verification and unauthorized redistribution, a digital image copyright protection method based on blockchain and zero trust mechanism was proposed. Firstly, after the copyright owner signs with the elliptic curve digital signature algorithm (ECDSA), the signature and copyright information are encrypted with the elliptic curve cryptography (ECC) algorithm, and the ciphertext and the generated image hashing are uploaded to the blockchain; Then, the smart contract is called to authenticate the copyright owner, the similarity of the hash value is used to detect the infringement of the verified image, the MD5 key generated by the image hashing value is used to encrypt the detected image, the ciphertext and encrypted image are uploaded to the interplanetary file system (IPFS), and the corresponding storage address is returned to the blockchain. Consumers can download ciphertext and encrypted images in IPFS as needed after completing asset evaluation and paying when calling the dual-smart contract to initiate copyright transaction. Experimental results show that the proposed method can not only authenticate the identity, but also realize double encryption of the image and copyright information. It can prevent the unauthorized use and redistribution of digital content, and improve the overall security of the image copyright protection system.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 61862041). The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.

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Correspondence to Qiu-yu Zhang or Guo-rui Wu.

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Zhang, Qy., Wu, Gr., Yang, R. et al. Digital image copyright protection method based on blockchain and zero trust mechanism. Multimed Tools Appl 83, 77267–77302 (2024). https://doi.org/10.1007/s11042-024-18514-3

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