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Web"],"published-print":{"date-parts":[[2026,2,28]]},"abstract":"<jats:p>With the rapid evolution of the Decentralized Web (DWeb), decentralized technologies have paved new avenues for Web3 applications and the authentication of digital assets. Among them, Non-Fungible Tokens (NFTs) have gained significant popularity due to their immutability and uniqueness, reshaping the landscape of artistic creation, marketing, and intellectual property protection. However, current blockchain-based NFT implementations still face core challenges within decentralized architecture: how to maintain decentralization while ensuring the visual uniqueness of digital assets and reducing storage costs. The rampant issue of duplication undermines the scarcity of digital art and erodes market confidence in copyright authenticity. Moreover, high gas fees and energy consumption further hinder the widespread adoption of NFTs, while reliance on external storage solutions like InterPlanetary File System (IPFS) introduces risks of data instability and loss. To address these challenges, this article presents the UniqueNFT framework, a novel architecture that deeply integrates blockchain oracles with decentralized storage verification mechanisms. The framework achieves three key technological breakthroughs: Using image inversion and generation techniques based on Encoder for Editing (E4E) and StyleGAN3, it extracts compact and expressive semantic features from NFT images, enabling efficient data compression and significantly reducing on-chain storage volume; The Crypto-Mask algorithm, by utilizing the hash value of blockchain user information (user-controlled SHA-256 digest of Ethereum address, user nickname, and registration time), ensures the visual uniqueness of NFTs; A smart contract extension compatible with the ERC721 standard, demonstrating UniqueNFT\u2019s seamless integration within the blockchain ecosystem. By leveraging the technologies of the Decentralized Web, our framework represents an important step forward in enhancing the security and uniqueness of digital assets. It not only innovatively resolves the issues of NFT duplication and homogenization but also injects new vitality and long-term momentum into the creation of a trusted, sustainable blockchain-based digital asset ecosystem.<\/jats:p>","DOI":"10.1145\/3779414","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T22:29:03Z","timestamp":1764973743000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["UniqueNFT: Uniqueness Protection of Digital Assets in Decentralized Web"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7515-103X","authenticated-orcid":false,"given":"Kun","family":"Yang","sequence":"first","affiliation":[{"name":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University","place":["Shenzhen, China"]},{"name":"Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6438-3790","authenticated-orcid":false,"given":"Haihan","family":"Duan","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University","place":["Shenzhen, China"]},{"name":"Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1095-0971","authenticated-orcid":false,"given":"Yubo","family":"Zhao","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University","place":["Shenzhen, China"]},{"name":"Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2772-4779","authenticated-orcid":false,"given":"Jiale","family":"Cheng","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University","place":["Shenzhen, China"]},{"name":"Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8694-4245","authenticated-orcid":false,"given":"Runhao","family":"Zeng","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University","place":["Shenzhen, China"]},{"name":"Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4952-699X","authenticated-orcid":false,"given":"Xiping","family":"Hu","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University","place":["Shenzhen, China"]},{"name":"Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing","place":["Shenzhen, China"]},{"name":"School of Medical Technology, Beijing Institute of Technology","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,2,18]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00453"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00832"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00664"},{"key":"e_1_3_2_5_2","first-page":"204","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Alaluf Yuval","year":"2022","unstructured":"Yuval Alaluf, Or Patashnik, Zongze Wu, Asif Zamir, Eli Shechtman, Dani Lischinski, and Daniel Cohen-Or. 2022. 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