Precognito: The Emergence of Blockchain & Machine Learning-Based for Student Record Authentication System

Education is advancing faster than ever before as a result of technological advancements. Two issues brought on by technological advancements are fake transcripts and fake degrees, both of which are mostly due to data security flaws. 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. By storing student data on the Blockchain and leveraging machine learning techniques for precise analysis, the technology can prevent additional fraud and uncertainty in student achievements and 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 decentralized and immutable alumni database that contains verified and transparent academic records. Furthermore, this system gives employers a place to check the legitimacy 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.

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Institutions

Publication Details

Journal
Journal of Advanced Research in Applied Sciences and Engineering Technology
Published
2024-10-07
DOI
https://doi.org/10.37934/araset.55.1.125140
Citations
2
Primary Topic
Digital and Cyber Forensics
Type
article
Field-Weighted Citation Impact
1.56
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article

Precognito: The Emergence of Blockchain & Machine Learning-Based for Student Record Authentication System

Rawad Abdulghafor, Norzariyah Yahya, Mohammed Mohammed, Sheikh Mohammad Tahsin Murtaj et al.
2 citations
Journal of Advanced Research in Applied Sciences and Engineering Technology
Digital and Cyber Forensics
1.56
article

Precognito: The Emergence of Blockchain & Machine Learning-Based for Student Record Authentication System

Rawad Abdulghafor, Norzariyah Yahya, Mohammed Mohammed, Sheikh Mohammad Tahsin Murtaj, Abubakar Abubakar Yusif
article en
2 citations

Abstract

Education is advancing faster than ever before as a result of technological advancements. Two issues brought on by technological advancements are fake transcripts and fake degrees, both of which are mostly due to data security flaws. 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. By storing student data on the Blockchain and leveraging machine learning techniques for precise analysis, the technology can prevent additional fraud and uncertainty in student achievements and 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 decentralized and immutable alumni database that contains verified and transparent academic records. Furthermore, this system gives employers a place to check the legitimacy 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.

Journal of Advanced Research in Applied Sciences and Engineering TechnologyVol. 55(1)
Arab Open University (OM), International Islamic University Malaysia (MY)
Openalex Percentile: Top 11%
Digital and Cyber Forensics
1.56
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