University Links: Home Page | Site Map
Covenant University Repository


Ubaka-Okoye, Millicent N. and Covenant University, Theses (2022) A MODEL FOR SECURING E-EDUCATIONAL DATA FROM INSIDER THREATS USING BLOCKCHAIN TECHNOLOGY. ["eprint_fieldopt_thesis_type_phd" not defined] thesis, Covenant University Ota.

[img] PDF
Download (385kB)


Personnel with authorization and system administrator’s privileges to the institution's secret information or Internet protocol (IP) addresses are capable of causing internal threats. There is, therefore, the need for institutions to provide a protection mechanism towards detecting insider threats occurrence route. Educational data should be upheld with the utmost integrity. Insider threats have harmed large educational institutions such as national examination boards, amongst others. Furthermore, security concerns in standardized school examinations, like insider threat, has always been a major problem that is yet to be fully addressed in educational institutions. The objective of this research is to build a model using Blockchain technology to protect e-educational data against insider threats. The methodology and techniques engaged include Blockchain Technology, Trust Function Model, Asymmetric Cryptology Model, Netlogo Model App, Ethereum, Proof of Authority Front end implementation using JavaScript, MetaMask, Microsoft Visual Studio, MongoDB, Remix, and Ganache for the backend dashboard web application. The experimental findings indicate that Blockchain system rate of recurrence of insider threat is about 30% minimum when compared with the existing model that has 70%. The developed Blockchain model can handle up to one thousand operational transactions with ease to reduce insider threats.

Item Type: Thesis (["eprint_fieldopt_thesis_type_phd" not defined])
Uncontrolled Keywords: Blockchain Technology, Education Data, Data Security, Insider Threats, Online Network, Privacy, Proof of Authority (POA), Trust Model.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: nwokealisi
Date Deposited: 15 Feb 2023 14:20
Last Modified: 15 Feb 2023 14:20

Actions (login required)

View Item View Item