Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/116150
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dc.contributorDepartment of Computing-
dc.creatorLiu, H-
dc.creatorCao, J-
dc.creatorCao, Y-
dc.creatorBai, D-
dc.creatorLiang, J-
dc.creatorLi, R-
dc.date.accessioned2025-11-25T03:57:17Z-
dc.date.available2025-11-25T03:57:17Z-
dc.identifier.issn1386-7857-
dc.identifier.urihttp://hdl.handle.net/10397/116150-
dc.language.isoenen_US
dc.publisherSpringer New York LLCen_US
dc.rights© The Author(s) 2025en_US
dc.rightsOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Liu, H., Cao, J., Cao, Y. et al. EdenDID: an edge computing and blockchain-based decentralized identity system for Web3 applications and DePIN. Cluster Comput 28, 1048 (2025) is available at https://doi.org/10.1007/s10586-025-05746-7.en_US
dc.subjectBlockchainen_US
dc.subjectDecentralized Identityen_US
dc.subjectDePINen_US
dc.subjectEdge Computingen_US
dc.subjectWeb3en_US
dc.titleEdenDID : an edge computing and blockchain-based decentralized identity system for Web3 applications and DePINen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume28-
dc.identifier.issue16-
dc.identifier.doi10.1007/s10586-025-05746-7-
dcterms.abstractBlockchain wallet manages decentralized identities in Web3, which allows users to identify themselves in a verifiable yet anonymous manner by digital signatures. However, native wallet scheme has been proven vulnerable to Sybil attacks in practice, where adversaries can easily create large numbers of controlled wallets at a low cost to undermine Web3 applications. To this end, many solutions are proposed for mitigating Sybil attacks. Nevertheless, they typically rely on either costly specialized biometric hardware or behavior-based heuristics that can be easily bypassed. In this paper, we introduce EdenDID, the first trinity-bound identity management system that uniquely binds human user, wallet address, and physical device into a unified framework. EdenDID combines edge-based video recognition, on-chain transactional activity analysis, and device computational power verification to establish a decentralized Proof-of-Trustworthiness consensus. The system provides compliant users with a trusted, verifiable credential to prove their unique identity. We prototype low-cost Eden Devices and deploy them on a Layer-2 blockchain network. Our experiments demonstrate the low end-to-end latency and robust resistance performance to Sybil attacks. Moreover, we present a case study to show how EdenDID can mitigate virtual-hardware fraud in DePIN, in which EdenDID successfully binds the user, wallet, and device uniquely, thus preventing users from binding multiple wallets or devices.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationCluster computing, Dec. 2025, v. 28, no. 16, 1048-
dcterms.isPartOfCluster computing-
dcterms.issued2025-12-
dc.identifier.scopus2-s2.0-105019227913-
dc.identifier.eissn1573-7543-
dc.identifier.artn1048-
dc.description.validate202511 bcch-
dc.description.oaRecord of Versionen_US
dc.identifier.FolderNumberOA_TAen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextOpen access funding provided by The Hong Kong Polytechnic University. This work is partially supported by HK RGC Theme-based Research Scheme (No.: T43-513/23-N), NSFC/HK RGC Collaborative Research Scheme (No.: CRS_PolyU501/23) and the Research Institute for Artificial Intelligence of Things, The Hong Kong Polytechnic University, HK.en_US
dc.description.pubStatusPublisheden_US
dc.description.TASpringer Nature (2025)en_US
dc.description.oaCategoryTAen_US
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