Abstract
E-portfolios, or electronic portfolios, have recently gained popularity as a means for students and continuous learners to present their skills, accomplishments, and other relevant information in an online format. To confirm learning outcomes, e-portfolios need secure, dependable, and privacy-protecting systems for issuing and verifying credentials. When any client changes their document, designs present in help are altered, and it is imperative to refresh them in setup data handling frameworks. Considering the unchanging nature of the text, it is a mind-boggling undertaking to refresh the changed substance in web-related applications. Making computerized antiques is one of the significant issues to be evident and solid in updated content. Existing frameworks give private organizations comprehensive, concentrated arrangements that depend on trusted outsiders to issue and confirm accreditations. In addition, they need to give students the tools to take ownership of and share the material in their e-portfolios with other organizations, which increases the potential for forgery and bogus credentials. This paper proposes the Trusty URI Learning-Based Secure Blockchain Management Schema (TURILSBMS). This framework ensures the legitimacy and uprightness of client certifications. What is more, the information relates to an e-portfolio. While unquestionable cases are used for e-portfolio qualification evidence confirmation and check, decentralized IDs and undeniable certificates are used for client profile differentiating proof, verification, and approval. We have planned and carried out a model of the proposed plot utilizing a Quorum consortium blockchain network. Considering the assessments, our arrangement is attainable, secure, and protective. Compared to traditional approaches, the proposed approach gives better privacy-based immutable digital artifact creation over nanopublication.
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Shaik, N., Reddy, E.S. Trusty URI learning-based secure blockchain management for making verifiable and reliable digital artifacts. Soft Comput 27, 16389–16399 (2023). https://doi.org/10.1007/s00500-023-08511-3
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DOI: https://doi.org/10.1007/s00500-023-08511-3