QuantumShield: Multilayer Fortification for Quantum Federated Learning
Dev Gurung, Shiva Raj Pokhrel
TL;DR
QuantumShield addresses the risk that classical cryptography becomes insecure in a quantum era by proposing a multi-layer quantum-secure QFL framework. It integrates QKD, quantum teleportation, KEMs, and PQC to secure key exchange, state transfer, and authenticity during federated learning, with theoretical analyses and extensive experiments on Iris and Genomic datasets. The work details four protocol variants (QKD-QFL, TP-QFL, KEM-QFL, PQC-QFL), analyzes their security guarantees (BB84-based QKD, no-cloning teleportation, IND-CCA/IND-CPA KEM, and PQC SUF-CMA), and reports protocol- and dataset-dependent performance. This framework provides a concrete pathway toward practical, quantum-resilient federated learning suitable for deployment in quantum-enabled networks.
Abstract
In this paper, we propose a groundbreaking quantum-secure federated learning (QFL) framework designed to safeguard distributed learning systems against the emerging threat of quantum-enabled adversaries. As classical cryptographic methods become increasingly vulnerable to quantum attacks, our framework establishes a resilient security architecture that remains robust even in the presence of quantum-capable attackers. We integrate and rigorously evaluate advanced quantum and post-quantum protocols including Quantum Key Distribution (QKD), Quantum Teleportation, Key Encapsulation Mechanisms (KEM) and Post-Quantum Cryptography (PQC) to fortify the QFL process against both classical and quantum threats. These mechanisms are systematically analyzed and implemented to demonstrate their seamless interoperability within a secure and scalable QFL ecosystem. Through comprehensive theoretical modeling and experimental validation, this work provides a detailed security and performance assessment of the proposed framework. Our findings lay a strong foundation for next-generation federated learning systems that are inherently secure in the quantum era.