Murtaj, Sheikh Mohammad Tahsin and Mohammed, Mohammed and Abubakar Yusif, Abubakar and Yahya, Norzariyah and Abdulghafor, Rawad (2024) Precognito: the emergence of blockchain & machine learning-based for student record authentication system. Journal of Advanced Research in Applied Sciences and Engineering Technology, 55 (1). pp. 125-139. E-ISSN 2462-1943
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Abstract
Education is progressing more rapidly than ever due to technological advancements. Technological advancements have led to two problems: counterfeit transcripts and degrees, primarily caused by data security vulnerabilities. Despite technological advancement, many domains have not been sufficiently investigated, and there will always be room for improvement. This project aims to create a tool that combines two cutting-edge technologies, machine learning (ML) and blockchain, to combat problems like degree and transcript forgery. The technology can prevent additional fraud and uncertainty in student achievements by storing student data on the Blockchain and leveraging machine learning techniques for precise analysis. It can enable accurate prediction of future employment opportunities for graduates. Machine learning algorithms are used to train and make accurate predictions, and the requisite data are retrieved from a Blockchain ledger. PRECOGNITO will equip the institution with a decentralised and immutable alumni database that contains verified and transparent academic records. Additionally, this system provides employers with a means to verify the validity of their employees’ academic credentials. Moreover, PRECOGNITO allows students to upload their academic credentials to social media and professional networking sites like LinkedIn. With this system, recruiters may easily locate verified student information.
| Item Type: | Article (Journal) |
|---|---|
| Additional Information: | 5066/119780 |
| Uncontrolled Keywords: | Precognito, blockchain, machine learning |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science |
| Depositing User: | Dr. Norzariyah Yahya |
| Date Deposited: | 26 Feb 2025 17:26 |
| Last Modified: | 27 Feb 2025 10:55 |
| URI: | http://irep.iium.edu.my/id/eprint/119780 |
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