Please use this identifier to cite or link to this item: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31765
Title: Learners’ Data Privacy Preserving Scheme (LDPPS) in Mobile Learning System: A Permissioned Blockchain Solution
Authors: Muhammad, M. K.
Oyefolahan, I. O.
Olaniyi, O. M.
Adebayo, O. J.
Lasotte, Y. B.
Oluwasayo, A
Keywords: Journal of Science, Technology, Mathematics and Education (JOSTMED) 20(1)
Issue Date: Mar-2025
Publisher: Journal of Science, Technology, Mathematics and Education (JOSTMED) 20(1)
Citation: 2. Muhammad M.K., Oyefolahan I.O., Olaniyi O.M., Adebayo O.J., Lasotte Y. B, & Oluwasayo A. (2025). Learners’ Data Privacy Preserving Scheme (LDPPS) in Mobile Learning System: A Permissioned Blockchain Solution. Journal of Science, Technology, Mathematics and Education (JOSTMED) 20(1) March, 2025, ISSN: 0748-4710, Page 106-117.
Abstract: The use of learning technology has significantly improved the face-to-face learning environments and the general adoption of the open and distance learning (ODL), which augmented the classical learning systems. ODL Data Lake serves as primary digital repositories for materials and resources for several individuals for the purpose of teaching and learning activities among staff, learners’ and institutions. There are cases of insecurity arising from learners’ interaction with learning resources from different locations. These are often possible because of vulnerable, weak authentication schemes and the difficulty confirming learners’ identity. This further echoed the need for adequate security tool in m-learning environments to forestall present and future issues. Therefore, the article attempted to develop an appropriate access and authorisation scheme based on blockchain technology for preserving privacy of learners’ sensitive data) enrolled in MLS. On the Permissioned Blockchain solution, Learners’ Data Privacy Preserving Scheme runtime (or processing time), the proposed hashing scheme (4.95%) was higher than SHA-1 (2.30%), SHA-224 (2.23%), SHA-256 (4.28%), SHA-384 (3.51%), and SHA-512 (2.67%) for processing time. Conversely, the proposed hashing scheme trailed behind high-performing hashing schemes: BCrypt (45.56%), and PBE (34.50%), which revealed that, higher runtime values offered better privacy of information on the blockchain technology and its functions. The contributions / findings of the study were that approach helps maintain scalability while preserving data privacy. Decentralised nature ensures that no single entity has control over the learners' data, enhancing privacy and feature crucial for preserving the integrity of learners' data and preventing unauthorized modifications. Finally, create a secure and privacy-preserving environment for learners' data, ensuring that it remains confidential, tamper-proof, and accessible only to authorised parties.
URI: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31765
Appears in Collections:Computer Science



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