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International Conference on Smart Systems and Inventive Technology (ICSSIT)

AI-Driven Adaptive Control for Scalable Twin-Field Quantum Key Distribution Networks

Narmatha V, P. Joshua Reginald

Published Jul 1, 2026• 0 citations
Publisher
DOI
10.1109/icssit69151.2026.11656492

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Quantum key distribution (QKD) is a key application in quantum communication, enabling secure key exchange between parties using quantum states. Twin-field (TF) QKD offers a promising solution that surpasses the repeaterless limits, and its measurement-device-independent nature makes it suitable for star-type network architectures. In this work, we propose a scalable TF-QKD network with adaptable architecture, where users prepare quantum signals and send them to network nodes. These nodes use an optical switch to route the signals to multi-user measurement units, enabling secure key distribution among arbitrary users and adapting to complex connection demands of the network. A proof-of-principle demonstration with three users successfully achieved secure key sharing over simulated link losses of up to 303030 dB, with an average rate of 19.5719.5719.57 bit/s. Additionally, simulations show that the proposed architecture can achieve a total secure key rate of 4.84×1044.84 \times 10^{4}4.84×104 bit/s at 100100100 km in a symmetric 323232-user network. This approach represents a significant advancement in the topology of untrusted-node QKD networks and holds promise for practical, large-scale applications in secure communication.
The rapid evolution of communication networks, driven by the expansion of heterogeneous environments such as 6G, Internet of Things (IoT), and edge computing, has exposed a critical research gap in the lack of unified frameworks that jointly address intelligent network control and quantum-resilient security. Existing networking protocols were originally designed under static configurations and classical security assumptions, making them increasingly inadequate for dynamic, large-scale, and intelligent infrastructures exposed to quantum-enabled threats. At the same time, the emergence of Quantum Computing (QC) introduces severe security risks, as widely used cryptographic mechanisms supporting protocols such as Transport Layer Security (TLS) and Internet Protocol Security (IPsec) become vulnerable to quantum attacks. This paper presents a structured survey based on a systematic classification of recent literature across AI-enabled networking, Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD), and protocol-level integration approaches. The review categorizes existing works into AI-driven network optimization, quantum-resilient security mechanisms, and hybrid AI–QRC architectural frameworks, enabling a unified comparison of design strategies and deployment models. Furthermore, this survey analyzes how Artificial Intelligence (AI) techniques enable autonomous network operations while Quantum-Resilient Cryptography (QRC) approaches provide post-quantum security guarantees, highlighting their complementary roles in next-generation network design. The study further synthesizes key findings for a tightly coupled AI–QRC co-design, which remains an open challenge due to mismatched assumptions in control latency, cryptographic overhead, and protocol adaptability. Additionally, this review emphasizes the need for integrated frameworks that combine intelligence and quantum security to develop adaptive, scalable, and resilient network protocols for the post-quantum era.
With cloud computing, users have easy and on-demand access to applications and services, catering to a dynamic group of users whose demographics evolve over time. To facilitate secure data transmission while safeguarding privacy, we propose a scalable and flexible sharing framework tailored for cloud environments, which allows users to communicate data anonymously using group signature and dynamic broadcast encryption techniques. Additionally, the convergence of AI and quantum networks enhances this framework by offering unprecedented capabilities in business and medicine through secure and high-speed data transmission. Advanced cryptographic techniques such as quantum key distribution (QKD) and AI-driven dynamic access control ensure data confidentiality and integrity amidst frequent changes in user groups. Our comprehensive solution seamlessly adapts to varying group sizes, integrating cloud computing, AI, and quantum networks to provide a robust and efficient data-sharing framework for dynamic environments.