{"id":11727,"date":"2026-09-13T22:42:38","date_gmt":"2026-09-13T14:42:38","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=11727"},"modified":"2026-09-13T23:17:19","modified_gmt":"2026-09-13T15:17:19","slug":"jase-202612-35-036","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202612-35-036","title":{"rendered":"A Blockchain-Based Model for Copyright and Privacy Protection of Industrial New Media Content"},"content":{"rendered":"\n
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<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 35<\/a><\/p>\n<\/div>\n\n\n\n

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Si Wu<\/i><\/a><\/p>\n\n\n\n

School of Journalism and Communications, Zhoukou Normal University, Zhoukou, 466000 Henan, China<\/p>\n<\/div>\n\n\n\n

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Received: July 04, 2026
Accepted: September 29, 2026
Publication Date: September 11, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Operation Flow of the Proposed Model <\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation: BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202612_35.036<\/a> <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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Industrial new media content such as equipment operation videos, technical manuals, engineering drawings, and factory livestreams faces growing copyright and privacy challenges from complex infringement methods, high on-chain storage pressure, and the risk of exposing creators’ identities and proprietary technical information. This study proposes a blockchain-based copyright and privacy protection model that ensures credible copyright evidence while preserving privacy and scalability. Built on a Hyperledger Fabric consortium blockchain, the model follows a layered “content processing-on-chain registration – privacy authorization – off-chain storage – copyright verification” architecture, integrating multimodal copyright fingerprinting, dynamic pseudo-identity generation, attribute-based access control with trust\/risk\/frequency scoring, hybrid on-chain-off-chain storage, and distributed indexing. Large-scale simulation with millions of content items shows a registration latency of 490 ms, throughput of 2120 TPS, retrieval response time of 430 ms, storage overhead of 280 GB, verification accuracy of 94.5%, and an F1 score of 0.76 under 50% tampering. The privacy leakage rate is reduced to 9.4%, with an 84.6% unauthorized-access interception rate under severe attack. These results indicate improved copyright robustness, stronger privacy protection, and better scalability, supporting staged deployment on consortium-based industrial new media platforms without exposing original content or real identities on-chain.<\/p>\n\n\n\n

Keywords: Industrial new media content; Blockchain; Copyright protection; Privacy protection; Multimodal copyright fingerprint; Dynamic pseudo-identity.<\/em><\/p>\n\n\n\n

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