Providing secure and scalable cryptographic key distribution in dynamic, infrastructure-less environments remains a major challenge. This work investigates the feasibility and performance of dynamic drone-based mesh networks for Quantum Key Distribution (QKD). A detailed Python-based simulation model was developed, incorporating realistic quantum and classical communication channels, multiple drone mobility strategies, key management mechanisms (including revocation), and simulated adversarial conditions such as jamming and interception. The objectives were to model dynamic environments, evaluate key distribution efficiency, and analyze the influence of configuration and adversarial factors on key availability. Results show that adversarial attacks substantially reduce key availability, emphasizing the need for robust security and adaptive key management. Directed mobility strategies demonstrated improved distribution efficiency compared to random movement. Overall, the findings indicate that dynamic drone mesh networks hold strong potential for scalable QKD deployment in challenging, mobile environments, though performance and resilience strongly depend on network configuration, link quality, and mitigation strategies.
Providing secure and scalable cryptographic key distribution in dynamic, infrastructure-less environments remains a major challenge. This work investigates the feasibility and performance of dynamic drone-based mesh networks for Quantum Key Distribution (QKD). A detailed Python-based simulation model was developed, incorporating realistic quantum and classical communication channels, multiple drone mobility strategies, key management mechanisms (including revocation), and simulated adversarial conditions such as jamming and interception. The objectives were to model dynamic environments, evaluate key distribution efficiency, and analyze the influence of configuration and adversarial factors on key availability. Results show that adversarial attacks substantially reduce key availability, emphasizing the need for robust security and adaptive key management. Directed mobility strategies demonstrated improved distribution efficiency compared to random movement. Overall, the findings indicate that dynamic drone mesh networks hold strong potential for scalable QKD deployment in challenging, mobile environments, though performance and resilience strongly depend on network configuration, link quality, and mitigation strategies.
Providing secure and scalable cryptographic key distribution in dynamic, infrastructure-less environments remains a major challenge. This work investigates the feasibility and performance of dynamic drone-based mesh networks for Quantum Key Distribution (QKD). A detailed Python-based simulation model was developed, incorporating realistic quantum and classical communication channels, multiple drone mobility strategies, key management mechanisms (including revocation), and simulated adversarial conditions such as jamming and interception. The objectives were to model dynamic environments, evaluate key distribution efficiency, and analyze the influence of configuration and adversarial factors on key availability. Results show that adversarial attacks substantially reduce key availability, emphasizing the need for robust security and adaptive key management. Directed mobility strategies demonstrated improved distribution efficiency compared to random movement. Overall, the findings indicate that dynamic drone mesh networks hold strong potential for scalable QKD deployment in challenging, mobile environments, though performance and resilience strongly depend on network configuration, link quality, and mitigation strategies.
This project presents a comprehensive simulation platform for secure communication in autonomous drone networks, leveraging quantum key distribution (QKD) protocols alongside hybrid cryptography techniques. It models realistic physical channel conditions, including atmospheric turbulence and optical losses, and evaluates various quantum hacking attack scenarios such as intercept-resend, photon number splitting, and Trojan horse attacks. The platform supports multiple QKD protocols (BB84, B92, SARG04, E91, CVQKD) and provides detailed performance metrics including key rate, quantum bit error rate (QBER), and privacy amplification. Additionally, it integrates drone flight dynamics, battery models, and environmental factors to enable end-to-end security analysis in mobile quantum networks. The source code, simulation scripts, configuration files, and documentation are openly available and aimed at advancing research and education in quantum secure communications.
Abstract The increasing demand for secure communications in mobile and critical infrastructure networks has led to the emergence of Quantum Key Distribution (QKD) as a promising technique for enhancing cryptographic security in next-generation systems. This paper reviews recent progress in integrating QKD within mobile and wireless networks. It focuses on key enabling technologies, such as Software-Defined Networking (SDN), satellite-based, and aerial networks. The paper critically analyzes how these frameworks can address evolving security requirements in sixth-generation (6G) networks and smart city infrastructures. Additionally, it examines the role of Machine Learning (ML) in improving QKD performance and adaptability. Challenges such as key management, mobility support, scalability, and interoperability are explored. These challenges help identify current barriers and research directions. By consolidating developments and highlighting unresolved issues, this study offers researchers valuable insights. It discusses the convergence of quantum communication and advanced mobile architectures, facilitating the design of secure and resilient future communication infrastructures.
Quantum Key Distribution (QKD) networks enable unconditionally secure key exchange using quantum mechanical principles. However, routing cryptographic keys across multi-hop quantum networks introduces challenges unique to quantum communication. This survey analyzes and classifies 26 routing strategies proposed between 2013 and 2024 for terrestrial, satellite, and hybrid QKD infrastructures. Dynamic, key-aware routing algorithms have been shown to reduce service rejection rates by 25-40% compared to static shortest-path methods by incorporating real-time key pool availability and link error rates. Multi-path strategies improve resilience against trusted-node compromise by distributing keys across disjoint routes, albeit with an increase in key consumption of 30-60%. SDN-based orchestration frameworks emerge as essential enablers of flexible, QoS-aware routing for hybrid networks integrating terrestrial fibers and intermittent satellite links. Critical research directions include reducing dependence on trusted nodes through quantum repeaters or post-quantum cryptography, developing standardized key management interfaces for interoperability, and adopting AI-driven predictive routing for adapting to fluctuating network states. This comprehensive synthesis of routing algorithms, performance trade-offs, and unresolved issues offers practical guidance for engineering secure, adaptable, and large-scale QKD networks capable of meeting real-world deployment demands.
The paper addresses the Quantum Networks (QN) performance with Quantum Key Distribution (QKD) protocols.The focus is on networks with multi-hop paths (multiple QKD links with intermediate nodes).QKD emerged as a promising technology to ensure unconditioned communications security by exploiting the Quantum Computing (QC) and quantum principles.While the Point-to-Point (P2P) QKD links are well understood for several QKD protocols, the challenges concern the development of QN with multiple intermediate nodes and links.The deployment of quantum-secure communication systems over very large distances requires multi-hop QN.This paper presents a simulation-based case study for multi-hop QKD networks, focusing on the performance evaluation and the Cyber Security implications.The framework could be used to evaluate end-to-end key generation rates, latency, and resilience under various network topologies and link conditions.This methodology will allow to properly investigate how the network-level security policies can be integrated with QKD protocols to detect and mitigate both passive and active attacks.One could find out the trade-offs between hop count, security margins, and throughput, providing insights into the design of robust and scalable quantumsecure communication infrastructures.This study will support the research about the integration of the QKD with the classical network management, conventional security mechanisms and advanced Cyber defense strategies.
The emergence of sixth-generation (6G) wireless networks introduces unprecedented requirements for ultra-secure, low-latency communication across heterogeneous space–air–ground integrated network (SAGIN). Existing drone communication frameworks including LoRaWAN, Long Term Evolution, and Ad Hoc mesh architectures exhibit critical vulnerabilities to eavesdropping, jamming, and quantum-computational attacks due to their reliance on classical cryptographic primitives. To address these challenges, this work presents the Quantum-Secured Adaptive Routing Algorithm (QSARA), a novel framework designed for 6G-enabled unmanned aerial vehicle (UAV) networks that integrates Quantum Key Distribution (QKD), Reconfigurable Intelligent Surfaces (RIS), and Joint Communication and Sensing (JCAS) to enhance information-theoretic security and real-time performance. The proposed framework employs a quantum-augmented dynamic graph model to represent UAV swarm networking and uses Proximal Policy Optimisation (PPO)-based deep reinforcement learning to optimise routing under adversarial and uncertain conditions. A multi-objective cost function jointly captures classical quality of service metrics, such as latency, bandwidth, and energy consumption alongside with quantum-layer security indicators, including quantum bit error rate, key pool entropy, and key availability. High-fidelity simulations with 500 mobile drones under diverse adversarial threats demonstrate that the proposed framework achieves a key establishment success rate of 96.2%, end-to-end latency of 23.7 milliseconds, energy consumption of 7.8 watt-hours, and a packet delivery ratio of 94.1%, outperforming state-of-the-art classical and quantum-aware baselines. These results position the QSARA as a scalable and quantum-resilient routing solution for mission-critical UAV networking in next-generation 6G smart mobility ecosystems.