Quantum-secured routing in drone communication for 6G-enabled smart mobility
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.
Authors
- Ghulam E Mustafa Abro (ORCID: https://orcid.org/0000-0003-1874-1889)
- Sana Hafeez (ORCID: https://orcid.org/0000-0003-4769-4284)
- Sufyan Ali Memon
- Haidawati Nasir
- Talha Ahmed Khan
- Imran Memon
Institutions
- Shahrekord University (IR)
- Aarhus University (DK)
- Aarhus University Hospital (DK)
- Sejong University (KR)
- Shah Abdul Latif University (PK)
- University of Kuala Lumpur (MY)
- Liverpool John Moores University (GB)
Publication Details
- Journal
- Scientific Reports
- Published
- 2026-02-19
- DOI
- https://doi.org/10.1038/s41598-026-36297-5
- Citations
- 1
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 104.69
Funders
- Aarhus Universitet
- King Fahd University of Petroleum and Minerals
- Universiti Kuala Lumpur