Quantum AI for cybersecurity in financial supply chains: Enhancing cryptography using random security generators

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.