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Post-Quantum Cryptographically-Secured Trusted Node for Quantum Key Distribution in a Deployed Network

Heming Huang, Yves Jaouën, Nicolas Fabre, Romain Alléaume, Jean-Sébastien Pegon, Thomas Camus, Martin Zuber, Jean‐Charles Faugère, Pierre-Enguerrand Verdier, Baptiste Lacour, Maxime Gautier, Thomas Rivera, Yoann Piétri, Matteo Schiavon, Amine Rhouni, Eleni Diamanti

Published Sep 2, 2024• 0 citations
OpenAlex

Abstract

Objective:Reduce the security risks associated with the usage of trusted nodes in a QKD network.Conclusion:The transported QKD key is secure agains honest-curious nodes at a lower key-rate cost than state-of-the-art.

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Abstract QKD (Quantum Key Distribution) promises information-theoretical security by using quantum states to generate shared cryptographic key material and to reveal eavesdropping attempts through unavoidable physical disturbances. The practical value of this promise depends not only on quantum technologies such as DV-QKD, CV-QKD, entanglement-based QKD, MDI-QKD, and Twin-Field QKD, but also on authentication, post-processing, implementation quality, and operational architecture. Fiber-optic, satellite, and free-space QKD each impose distinct limits on distance, key rate, trusted nodes, costs, and resistance to side-channel attacks.

SpringerBriefs in information security and cryptography•Jan 1, 2026•0 citations
Quantum Key Distribution (QKD) enables two distant users to exchange a secret key with information-theoretic security, based on the fundamental laws of quantum physics. While it is arguably the most mature application of quantum cryptography, it has inherent limitations in the achievable distance and the scalability to large-scale infrastructures. While the applicability of QKD can be readily increased with the use of intermediary trusted nodes, this adds additional privacy requirements on third parties. In this work, we present an efficient scheme leveraging a trusted node with lower privacy requirements thanks to the use of post-quantum cryptographic techniques, and implement it on a deployed fiber optic quantum communication network in the Paris area.
The technological maturity of Quantum Key Distribution (QKD) products have generated high demand for secure key distribution in transmitting sensitive data. To provide this service, long-haul network operators are exploring strategies for network-wide deployment of QKD devices while utilizing existing infrastructure. One approach is to place trusted nodes at existing in-line amplifier huts in the network. In this study, we present a near-optimal fiber span aggregation algorithm, which effectively minimizes the number of trusted nodes between Points-of-Presences (PoPs) in the network. In this study, we evaluate six different topological QKD network deployments and eight different technological QKD network deployments in terms of the total secure key rate, as well as the number of QKD fiber pairs deployed. Our results indicate that the span aggregation algorithm increases the distance between each trusted node by up to 20%, thereby reducing the overall number of trusted nodes. Capacity planning for various topologies and technology deployments on simulated Secure Application Entity (SAE) requests is undertaken. Our proposed capacity planning shows that a baseline deployment with span aggregation using a QKD device with a cut-off distance of 140 km can save up to 3 times the number of QKD deployed fibers as compared to a minimum spanning tree-based low-cost deployment.
Abstract QKD (Quantum Key Distribution) promises information-theoretical security by using quantum states to generate shared cryptographic key material and to reveal eavesdropping attempts through unavoidable physical disturbances. The practical value of this promise depends not only on quantum technologies such as DV-QKD, CV-QKD, entanglement-based QKD, MDI-QKD, and Twin-Field QKD, but also on authentication, post-processing, implementation quality, and operational architecture. Fiber-optic, satellite, and free-space QKD each impose distinct limits on distance, key rate, trusted nodes, costs, and resistance to side-channel attacks.