Quantum-AI Federated Clouds: A trust-aware framework for cross-domain observability and security

Olufemi, Omoniyi David (2025) Quantum-AI Federated Clouds: A trust-aware framework for cross-domain observability and security. World Journal of Advanced Research and Reviews, 26 (2). pp. 4098-4140. ISSN 2581-9615

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.