Advancing Scholarship Management : A blockchain-Enhanced Platform with Privacy-Secure Identities and AI-Driven Recommendations

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorNguyen-Hoang, Tu Anh
dc.contributor.authorHoang, Ngoc Cu
dc.contributor.authorHua, Phu Thien
dc.contributor.authorThi, Mong Thy Nguyen
dc.contributor.authorTa, Thu Thuy
dc.contributor.authorNguyen, Thu
dc.contributor.authorTan-Vo, Khoa
dc.contributor.authorDinh, Ngoc Thanh
dc.contributor.authorNguyen, Hong Tri
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.organizationVietnam National University Ho Chi Minh City
dc.contributor.organizationIndustrial University of Ho Chi Minh City
dc.date.accessioned2024-12-11T10:32:58Z
dc.date.available2024-12-11T10:32:58Z
dc.date.issued2024
dc.descriptionPublisher Copyright: © 2013 IEEE.
dc.description.abstractTraditional scholarship management systems are often marred by inefficiencies, a lack of transparency, and significant concerns regarding data privacy. These challenges hinder the equitable distribution of educational funds and obscure the scholarship allocation process. This study aims to address these issues by proposing a blockchain-based scholarship management platform. However, scalability issues are introduced along with blockchain-based solutions, for which zk-rollup offers a promising solution. The integration of Self-Sovereign Identity Zero-Knowledge Proof assures secure and private submission of scholarship applications, safeguarding student data while maintaining transparency in the verification process. Additionally, a machine learning model is employed to predict scholarship qualification, functioning as a recommendation system that identifies and prioritizes deserving students. This data-driven approach proactively eliminates barriers that potentially impede deserving students from accessing financial aid, such as administrative oversights or a lack of self-assurance in their qualifications. Our experimental findings confirm the effectiveness of zk-rollups in enhancing transaction efficiency, demonstrating a reduction in transaction confirmation time by approximately 63.6% and a decrease in transaction costs by nearly 90%. Besides, the machine learning model achieved a good performance rating, achieving a balanced accuracy of 86.75% and a mean average precision of 91.68% on a realistically imbalanced test set, reflecting real-world conditions.en
dc.description.versionPeer revieweden
dc.format.extent31
dc.format.mimetypeapplication/pdf
dc.identifier.citationNguyen-Hoang, T A, Hoang, N C, Hua, P T, Thi, M T N, Ta, T T, Nguyen, T, Tan-Vo, K, Dinh, N T & Nguyen, H T 2024, 'Advancing Scholarship Management : A blockchain-Enhanced Platform with Privacy-Secure Identities and AI-Driven Recommendations', IEEE Access, vol. 12, 3486078, pp. 168060-168090. https://doi.org/10.1109/ACCESS.2024.3486078en
dc.identifier.doi10.1109/ACCESS.2024.3486078
dc.identifier.issn2169-3536
dc.identifier.otherPURE UUID: 9ec32c3c-93c5-44e9-a96c-34b01f8c7296
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/9ec32c3c-93c5-44e9-a96c-34b01f8c7296
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85208142360&partnerID=8YFLogxK
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/166308477/Advancing_Scholarship_Management_A_Blockchain-Enhanced_Platform_With_Privacy-Secure_Identities_and_AI-Driven_Recommendations_pdfa2b.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/132231
dc.identifier.urnURN:NBN:fi:aalto-202412117709
dc.language.isoenen
dc.publisherIEEE
dc.relation.ispartofseriesIEEE Accessen
dc.relation.ispartofseriesVolume 12, pp. 168060-168090en
dc.rightsopenAccessen
dc.subject.keywordblockchain
dc.subject.keywordmachine learning
dc.subject.keywordscalability
dc.subject.keywordScholarship management
dc.subject.keywordzero-knowledge
dc.subject.keywordzk-rollup
dc.titleAdvancing Scholarship Management : A blockchain-Enhanced Platform with Privacy-Secure Identities and AI-Driven Recommendationsen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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