Design and deployment of zero-trust SMPC algorithm to enhance financial cybersecurity in small and medium scale supply chains in the United States
1 Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA.
2 Master of Finance Program, Hult International Business School, Cambridge, MA, USA.
3 School of Accounting, Economics and Finance, University of Portsmouth, England.
4 Department of Mechanical Engineering, University of Abuja, Nigeria.
5 Department of Software Engineering, Wipro Technologies, Tallinn Estonia.
6 School of Computer Science, University of Guelph, Ontario, Canada.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2024, 12(02), 853–864.
Article DOI: 10.30574/wjaets.2024.12.2.0351
Publication history:
Received on 09 July 2024; revised on 19 August 2024; accepted on 22 August 2024
Abstract:
This study designs and deploys zero-trust secure multiparty computation (SMPC) algorithms to enhance financial cybersecurity in small and medium-sized enterprises (SMEs) within the U.S. supply chain. Utilizing TensorFlow for machine learning, Apache Kafka for real-time data processing, and SMPC protocols, the proposed solution aims to provide robust, scalable, and economically viable cybersecurity measures. The research involved developing advanced machine learning-based zero-trust algorithms using TensorFlow, integrating SMPC protocols for secure data computation, and utilizing Apache Kafka for real-time data processing. The algorithms were tested and validated in both simulated and real-world SME environments to evaluate their effectiveness. The implementation of zero-trust SMPC algorithms led to significant improvements in various cybersecurity metrics. The true positive rate (TPR) increased from 85% to 98%, and the false positive rate (FPR) decreased from 5% to 1%. Average incident response time was reduced from 4 hours to 1 hour, and the average cost per incident decreased by 80%, with data loss per incident reduced by 90%. Compliance with GDPR and CCPA standards improved by 35.71% and 38.46%, respectively. User satisfaction increased by 41.67%, and system availability improved from 95% to 99%, with network latency decreasing by 60%. The results demonstrate that zero-trust SMPC algorithms significantly enhance financial cybersecurity for SMEs, reducing security incidents and financial impacts, improving regulatory compliance, and increasing user satisfaction and system performance. These advancements are crucial for strengthening the resilience and stability of the U.S. supply chain, supporting economic growth.
Keywords:
Zero-Trust Security; Secure Multiparty Computation (SMPC); Financial Cybersecurity; Small and Medium Enterprises (SMEs); Supply Chain Security
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0