Document Type
Article
Publication Date
2024
DOI
10.1080/17517575.2024.2351871
Publication Title
Enterprise Information Systems
Volume
18
Issue
6
Pages
727-750
Abstract
This study examines the importance of enterprise information systems that link several corporate organisations to share information about diverse products under high security settings. The primary goal of the proposed strategy is to create a direct link between product demand and production to minimise the impact of rising costs. The research motive to make a connection cannot be resolved without suitable data that shows both quantity and quality in each organisation unit. The suggested method is designed to deliver accurate data to authorised end users while preventing any data exposure to unauthorised users. Security cryptographic keys are utilised to create a data control method, and the blowfish algorithm is integrated with the projected system model to segregate data blocks for enterprise systems. Four scenarios are considered where the results show that by using the integrated model, it is feasible to increase the number of authorisation units to 88%, compared to the 75% attained with the current approach.
Rights
© 2024 The Authors
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Original Publication Citation
Selvarajan, S., Manoharan, H., Khadidos, A. O., Shankar, A., Khadidos, A. O., Viriyasitavat, W., & Xu, L. D. (2024). SSCM: A secured approach to supply chain management with control management using blowfish optimization. Enterprise Information Systems, 18(6), 727-750, Article 2351871. https://doi.org/10.1080/17517575.2024.2351871
Repository Citation
Selvarajan, Shitharth; Manoharan, Hariprasath; Khadidos, Alaa O.; Shankar, Achyut; Khadidos, Adil O.; Viriyasitavat, Wattana; and Xu, Li Da, "SSCM: A Secured Approach to Supply Chain Management Using Blowfish Optimization" (2024). Information Technology & Decision Sciences Faculty Publications. 99.
https://digitalcommons.odu.edu/itds_facpubs/99