As the reliance on Unmanned Aerial Vehicles (UAV), and UAV swarms increase in commercial, surveillance, and even defense, concerns regarding their network security are heightened too. Conventional cryptographic frameworks/protocols face significant vulnerabilities, such as eavesdropping, intrusion, and node-compromise that are further enhanced by emerging post-Quantum threats. The traditional countermeasures—detection of intrusion or corruption, dismissing corrupt or suspicious data, or abandoning the communication channel or the compromised UAV—are inefficient and unsustainable. It is like giving up on a lost troop, rather than reinforcing it to carry on the war. Hence, the necessity for dynamic, self-repairing security architectures is more urgent than ever. Quantum Graph Networks (QGN), an emerging concept in quantum information science, although still less practical, leverage quantum principles like entanglement and quantum walks to enhance network resilience. Existing research in quantum network topology, entanglement-assisted routing, and quantum key distribution (QKD) has laid the groundwork for secure communication in quantum networks. However, current frameworks lack autonomous adaptability and fail to dynamically heal compromised nodes while ensuring uninterrupted operation. In this paper, we propose a ‘Self-Healing’ Quantum Adaptive Graph (QAG)—a novel framework integrating quantum entanglement, evolving graph structures, and entropy-based resilience. The QAG would be able to autonomously detect compromised nodes, initiate self-healing through entangled state redistribution, and reconstruct network topology using quantum random walks and belief updates. Unlike traditional or modern graph-based security models, QAG enables nodes to dynamically adjust their entangled states, ensuring real-time security updates and seamless reconfiguration, even under extreme adversarial conditions. This framework can also be generalized and extended to satellite networks, Internet of Things (IoT) infrastructures, and high-assurance communication systems.

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Quantum Adaptive Graph: A Self-Healing Framework for Unmanned Aerial Vehicle (UAV) Swarms

  • Sourav Banerjee,
  • Anupam Bhattacharya

摘要

As the reliance on Unmanned Aerial Vehicles (UAV), and UAV swarms increase in commercial, surveillance, and even defense, concerns regarding their network security are heightened too. Conventional cryptographic frameworks/protocols face significant vulnerabilities, such as eavesdropping, intrusion, and node-compromise that are further enhanced by emerging post-Quantum threats. The traditional countermeasures—detection of intrusion or corruption, dismissing corrupt or suspicious data, or abandoning the communication channel or the compromised UAV—are inefficient and unsustainable. It is like giving up on a lost troop, rather than reinforcing it to carry on the war. Hence, the necessity for dynamic, self-repairing security architectures is more urgent than ever. Quantum Graph Networks (QGN), an emerging concept in quantum information science, although still less practical, leverage quantum principles like entanglement and quantum walks to enhance network resilience. Existing research in quantum network topology, entanglement-assisted routing, and quantum key distribution (QKD) has laid the groundwork for secure communication in quantum networks. However, current frameworks lack autonomous adaptability and fail to dynamically heal compromised nodes while ensuring uninterrupted operation. In this paper, we propose a ‘Self-Healing’ Quantum Adaptive Graph (QAG)—a novel framework integrating quantum entanglement, evolving graph structures, and entropy-based resilience. The QAG would be able to autonomously detect compromised nodes, initiate self-healing through entangled state redistribution, and reconstruct network topology using quantum random walks and belief updates. Unlike traditional or modern graph-based security models, QAG enables nodes to dynamically adjust their entangled states, ensuring real-time security updates and seamless reconfiguration, even under extreme adversarial conditions. This framework can also be generalized and extended to satellite networks, Internet of Things (IoT) infrastructures, and high-assurance communication systems.