Quantum AI for cybersecurity in financial supply chains: Enhancing cryptography using random security generators
1 Department of Mathematics, Lamar University, Beaumont, TX, USA.
2 Department of Mathematics, Science, and Social Studies Education, University of Georgia, Athens, USA
3 School of Accounting, Economics and Finance, University of Portsmouth, England.
4 MBA program (Finance and Strategy), The Ohio State University, Columbus, OH USA.
5 Joint School of Nanoscience and Nanoengineering, North Carolina A&T States University, NC, USA.
6 School of Computer Science, University of Guelph, Ontario, Canada.
7 MBA program, University Canada West, Vancouver, BC. Canada.
Research Article
World Journal of Advanced Research and Reviews, 2024, 23(01), 2443–2451
Publication history:
Received on 16 June 2024; revised on 21 July 2024; accepted on 24 July 2024
Abstract:
Securing the financial supply chains of the United States against sophisticated cyber threats is crucial in the digital age. This research integrates Quantum Random Number Generators (QRNGs) and Artificial Intelligence (AI) to enhance cybersecurity in financial supply chains. QRNGs leverage quantum mechanics to generate truly random numbers, essential for creating secure cryptographic keys, addressing the vulnerabilities of traditional deterministic RNGs. Our results demonstrate the superior performance of the QRNG-based system compared to classical RNG systems. The QRNG showed high entropy and unpredictability, passing NIST SP800-22 and Diehard tests with significantly higher rates. The AI component achieved high precision and recall in detecting cyber threats, enhancing the system's real-time security capabilities. The combined QRNG and AI system exhibited faster encryption and decryption speeds, lower latency, and higher resistance to predictive, quantum, and brute-force attacks. This research underscores the critical importance of adopting QRNGs and AI to secure financial supply chains. The integrated system offers robust cryptographic protection and real-time threat detection, providing a comprehensive solution to mitigate cyber threats. These findings highlight the potential of QRNG and AI technologies to revolutionize cybersecurity in the financial sector, ensuring the integrity and confidentiality of financial transactions and protecting critical financial infrastructure.
Keywords:
Quantum computing; Artificial Intelligence; Finance Cryptography; Random Number generator
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Copyright information:
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