[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120350-en":3,"doc-seo-120350-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120350,1099514067438,"River Wang","https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542",8,"Research & Report","Precognito: The Emergence of Blockchain - and Machine Learning-Based for Student Record Authentication System","Education accelerates through rapid technological advancement, yet counterfeit transcripts and degrees persist due to data security vulnerabilities. Many educational research areas remain insufficiently explored, leaving room for stronger safeguards and more reliable assessment. The PRECOGNITO project combines machine learning and blockchain to deter transcript and degree forgery by storing verified student records on an immutable ledger and using ML for precise analysis, enabling trustworthy evaluation and future employment opportunity prediction.","Journal of Advanced Research in Applied Sciences and Engineering Technology 55, Issue 1 (2026) 125-140  \n\n|  | Journal of Advanced Research in Applied Sciences and Engineering Technology\u003Cbr>Journal homepage:\u003Cbr>[https://semarakilmu.com. my/journals/index.php/applied_sciences_eng_tech/index](https://semarakilmu.com. my/journals/index.php/applied_sciences_eng_tech/index)\u003Cbr>ISSN: 2462-1943 |  |  |\n| --- | --- | --- | --- |\n| Precognito: The Emergence of Blockchain & Machine Learning-Based for Student Record Authentication System\u003Cbr>Sheikh Mohammad Tahsin Murtaj1, Mohammed Mohammed1, Abubakar Abubakar Yusif1, Norzariyah Yahya1,*, Rawad Abdulghafor2\u003Cbr>1 Department of Computer Science, Kulliyah of Information and Communication Technology, International Islamic University Malaysia, 53100 Jln Gombak, Malaysia\u003Cbr>2 Faculty of Computer Studies (FCS), Arab Open University–Oman, Muscat P.O. Box 1596, Oman |  |  |  |\n| ARTICLE INFO |  | ABSTRACT |  |\n| Article history:\u003Cbr>Received 10 February 2024\u003Cbr>Received in revised form 19 September 2024 Accepted 10 October 2024\u003Cbr>Available online 15 January 2025 |  | 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 adecentralised 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 |  |\n| Keywords:\u003Cbr>Precognito; blockchain; machine learning |  | 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. |  |\n| 1. Introduction\u003Cbr>In today's automated society, the education industry leads in embracing innovative technologies, particularly blockchain and machine learning, which are seen as transformative forces with uses across multiple sectors. Blockchain and machine learning, among the most transformative technologies of the 21st century, are still not fully leveraged in education. This vital sector faces degree fraud, cybersecurity threats, and the disparity between academic credentials and job readiness skills. |  |  |  |\n\n* Corresponding author.  \n[E-mail address: norzariyah@iium.edu.my](E-mail address: norzariyah@iium.edu.my)  \n[https://doi.org/10.37934/araset.55.1.125140](https://doi.org/10.37934/araset.55.1.125140)  \nTo tackle these issues, we proposed and developed a PRECOGNITO system that integrates blockchain and machine learning to create a secure, transparent platform for storing, managing, and analysing student records. We hypothesise that this platform can alleviate degree fraud, secure student data, offer precise performance assessments, and connect students with suitable employers. By utilising a mixed-methods approach, we seek to assess the feasibility and effectiveness of our proposed solution.  \n2. Related Works  \nBlockchain technology in education has garnered interest, particularly in creating a secure global assessment platform to store and mana","cbCairHitRz8d0MI","https://ap.wps.com/l/cbCairHitRz8d0MI","pdf",2502875,1,15,"English","en",105,"# Article Overview\n## Abstract and Objectives\n## Introduction\n## Related Works","[{\"question\":\"What problem does PRECOGNITO address in education?\",\"answer\":\"PRECOGNITO targets counterfeit transcripts and degrees caused by data security vulnerabilities, aiming to reduce degree fraud and uncertainty in academic achievements.\"},{\"question\":\"How does PRECOGNITO use blockchain in student record authentication?\",\"answer\":\"It stores student data on a blockchain ledger to provide a decentralized, immutable, and transparent alumni database, enabling verification of academic credentials.\"},{\"question\":\"How does machine learning contribute to the system's outcomes?\",\"answer\":\"Machine learning models are trained on data retrieved from the blockchain to perform accurate predictions and analysis, including assessing performance and supporting forecasts of future employment opportunities.\"}]","Precognito: The Emergence of Blockchain - 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