Department of Computer Engineering, University of Fairfax, VA, United States.
World Journal of Advanced Research and Reviews, 2025, 26(02), 4098-4140
Article DOI: 10.30574/wjarr.2025.26.2.2074
Received on 16 April 2025; revised on 25 May 2025; accepted on 27 May 2025
The convergence of quantum computing, artificial intelligence (AI), and federated cloud architecture offers transformative potential for secure, scalable, and privacy-preserving data processing. Yet, trust management and cross-domain observability remain major challenges, particularly in decentralized, heterogeneous cloud environments. This paper introduces Quantum-AI Federated Clouds (QAIFC) a novel trust-aware framework that combines quantum-safe encryption, federated machine learning, and explainable AI to enable secure and observable operations across cloud domains. We present QFedSecure, a protocol suite leveraging lattice-based cryptography, quantum key distribution, and AI-driven anomaly detection to support trust propagation and policy enforcement. The framework features a dynamic trust model, observability protocol, and mechanisms for adversarial resilience. Simulations using Qiskit, TensorFlow Federated, and NS3 show up to 40% improvement in trust calibration and 55% increase in adversarial detection over baseline systems. This work advances the foundation for resilient, decentralized, and quantum-secure AI cloud ecosystems.
Post-Quantum Encryption; Quantum Key Distribution (QKD); Zero-Knowledge Proofs (ZKPs); Federated Learning (FL); Explainable AI (XAI); Anomaly Detection in FL; Dynamic Trust Scoring; Differential Privacy (DP); Zero Trust Architecture (ZTA);
Preview Article PDF
Omoniyi David Olufemi. Quantum-AI Federated Clouds: A trust-aware framework for cross-domain observability and security. World Journal of Advanced Research and Reviews, 2025, 26(2), 4098-4140. Article DOI: https://doi.org/10.30574/wjarr.2025.26.2.2074