Precognito: the emergence of blockchain & machine learning-based for student record authentication system
Year: 2024
Type: article
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.
Authors: Murtaj, Sheikh Mohammad Tahsin, Mohammed, Mohammed, Abubakar Yusif, Abubakar, Yahya, Norzariyah, Abdulghafor, Rawad
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7051924241
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