Nafiz Ahmed

Work place: Department of Computer Science and Engineering, American International University-Bangladesh, Dhaka-1229, Bangladesh

E-mail: anikkumarsaha08@gmail.com

Website:

Research Interests: Data Structures, Data Structures and Algorithms, Data Science, Blockchain technology

Biography

Nafiz Ahmed received his B.Sc. degree in Computer Science and Engineering from American International University-Bangladesh (AIUB) in 2023. His major was Software Engineering. His research interests include Software Engineering, Blockchain Technology, Data Science, Data Structures, and Algorithms.

Author Articles
Two Proposed Models for Securing Data Management for Enterprise Resource Planning Systems Using Blockchain Technology

By Nafiz Ahmed Anik Kumar Saha Mustafa Ahmad Arabi Sheikh Talha Jubayer Rahman Dip Nandi

DOI: https://doi.org/10.5815/ijieeb.2023.06.02, Pub. Date: 8 Dec. 2023

An Enterprise Resource Planning (ERP) system is a software application that serves as a centralized platform to streamline and automate organizational functions and share real-time data, facilitating efficient communication and collaboration. It provides an all-inclusive approach to managing and optimizing business processes, boosting efficiency, fostering cooperation, and giving an overall picture of how the organization is operating. However, the traditional centralized databases in ERP systems pose security concerns. Blockchain Technology can be an appealing alternative as it comes with immutable and decentralized data as well as enhanced security. This study focuses on two methods of securing data management in ERP systems: Organizing the distributed information using The Ralph Kimball data model and optimizing an individual block using Database Sharding. This study does an extensive examination to determine the effectiveness of both suggested strategies, comprising a detailed evaluation that highlights the benefits and limitations of both techniques. This paper intends to patch the security holes in ERP systems to safeguard sensitive data and mitigate risks.

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