Quantum-Resistant FAIL on Blockchain for Evaluation of Performance Metrics in Creation of Distributed Ledgers

Abstract

Abstract The emerging growth of Quantum computing has significant challenges to change the classical cryptographic protocols, the security of AI–Blockchain systems to provide long-term security and provide federated learning (FL) for current cryptographic systems. This paper introduces a new framework as Quantum-Resistant Federated AI on Blockchain (QFAIB) that integrates Post-Quantum Cryptography (PQC) algorithms with real-time Federated AI Learning (FAIL) on distributed ledgers creation. The proposed QFAIB ensures end-to-end data security and confidentiality, decentralized trust, and adaptive intelligence, resistant to quantum decryption attacks. Through the integration of hybridization of CRYSTALS-Kyber encryption to create challenging task, that makes the Dilithium digital signatures, and Zero-Knowledge Proofs (ZKP) for privacy-preserving model validation and decentralized federated AI models, the proposed QFAIB compared with baseline and evaluated as the performance metrics as data integrity verification accuracy (DIVA), auditing efficiency (AE), quantum resistance efficiency (QRE), privacy leakage reduction (PLR) and throughput (TT) in multi-cloud and IoT environments and this work proved that real time distributed ledger creations.