Random Security Generators with Enhanced Cryptography for Cybersecurity in Financial Supply Chains

Blockchains, like Ethereum, depend on a distributed system of collaborative servers referred to as inspectors or mine workers to validate transactions and generate novel legal blocks. In today's electronic world, it is critical to secure financial supply chains (FSCs) from complex cyber-attacks. This study combines Quantized Random Security Generators (QRSGs) with Artificial Intelligence (AI) to improve cybersecurity in FSC. QRSGs use quantum physics to produce random outcomes, which is critical for establishing safe cryptography credentials and resolving the flaws of regular predictable RSGs. This study found that the QRSG-based approach outperformed traditional RSG methods. The QRSG demonstrated strong entropy and uncertainty, transferring both NIST SP800-22 and Diehard examinations at much greater levels. The platform's real-time safety features were improved by the AI element's outstanding performance measures in identifying security breaches. More rapid decoding and encryption times, reduced delay, and increased resilience to brute-force, quantum, and prediction assaults were all demonstrated by the coupled QRSG and AI methods. This study emphasizes how crucial it is to use AI and QRSGs to safeguard FSCs. The combined platform provides a complete option to reduce cyber-attacks by offering strong cryptography security and real-time attack identification. These results demonstrate how QRSG and AI innovations can completely transform cybersecurity in the banking industry, safeguarding vital financial systems and guaranteeing the privacy and reliability of financial payments.