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dc.contributor.authorWang, Hao
dc.contributor.authorMa, Shenglan
dc.contributor.authorDai, Hong-Ning
dc.contributor.authorImran, Muhammad
dc.contributor.authorWang, Tongsen
dc.date.accessioned2019-11-06T14:12:34Z
dc.date.available2019-11-06T14:12:34Z
dc.date.created2019-10-07T10:58:29Z
dc.date.issued2019
dc.identifier.issn0167-739X
dc.identifier.urihttp://hdl.handle.net/11250/2626978
dc.description.abstractOpen banking brings both opportunities and challenges to banks all over the world especially in data management. A blockchain as a continuously growing list of records managed by a peer-to-peer network is widely used in various application scenarios; and it is commonly agreed that the blockchain technology can improve the protection of financial data privacy. However, current blockchain technology still poses some challenges in fully meeting the needs of financial data privacy protection. In order to address the existing problems, this paper proposes a new data privacy management framework based on the blockchain technology for the financial sector. The framework consists of three components: (1) a data privacy classification method according to the characteristics of financial data; (2) a new collaborative-filtering-based model; and (3) a data disclosure confirmation scheme for customer strategies based on the Nudge Theory. We implement a prototype and propose a set of algorithms for this framework. The framework is validated through field experiments and laboratory experiments.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleBlockchain-based data privacy management with Nudge theory in open bankingnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalFuture generations computer systemsnb_NO
dc.identifier.doi10.1016/j.future.2019.09.010
dc.identifier.cristin1734354
dc.description.localcode© 2019. This is the authors’ accepted and refereed manuscript to the article. Locked until 4.10.2021 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedfalse
cristin.fulltextpostprint
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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