Affiliations: [a] Ministry of Higher Education and Scientific Research, Baghdad, Iraq | [b] College of Technical Engineering, Imam Ja’afar Al-Sadiq University, Al-Muthanna, Iraq | [c] Informatics Institute for Postgraduate Studies/Iraqi Commission for Computer and Informatics, Baghdad, Iraq | [d] Department of Computer Science, Al-turath University College, Baghdad, Iraq | [e] Altoosi University College, Najaf, Iraq | [f] Department of Computer Technical Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq | [g] Medical Instrumentation Techniques Engineering Department, Al-Mustaqbal University College, Babylon, Iraq | [h] Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia | [i] Department of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad, Iraq
Correspondence:
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Corresponding author: Mustafa Musa Jaber, Informatics Institute for Postgraduate Studies/Iraqi Commission for Computer and Informatics, Baghdad 10021, Iraq. E-mails: Mustafa.jaber@turath.edu.iq and Musjaber28@outlook.com.
Abstract: Business intelligence is becoming more essential for supply chain administrators to make good decisions. The globalization of supply chains makes their management and control more challenging. Blockchain is a distributed digital ledger technology that guarantees traceability, transparency, and security and promises to ease global supply chain management issues. This paper proposes the Blockchain-assisted Secure Data Management Framework (BSDMF) for financial data handling for supply chain integrated business intelligence models. Analyzing, collecting, and demonstrating data could be important to a business, its supply chain performance, and sustainability. The blockchain can interrupt supply chain processes for improved finance handling, distributed management, and process automation. The study’s experimental result will help organizations deploy blockchain applications with intelligent business strategies to support supply chain management effectively. The simulation outcome has been implemented, and the recommended method achieves a computation time of fewer than 2 hours, an efficiency ratio of 97.4%, an error ratio of 94.1%, data authentication of 92.1%, and a data management ratio of 98.7%.
