The article examines the prospects of integrating quantum technologies into unmanned aerial vehicles (UAVs). Research on quantum technologies has been conducted in the development of new unmanned aircraft. Particular attention is given to quantum sensors for navigation, quantum optimization algorithms for autonomous control, and quantum key distribution (QKD) for secure communication. The research employs comparative analysis of classical and quantum sensors, a review of optimization algorithms (QAOA, VQE), and the principles of QKD. Laboratory and field test results are considered, along with the experience of international companies and startups. It is shown that quantum inertial sensors enable drift-free navigation even in “GPS-denied” environments. QKD ensures secure communication channels, while quantum optimization algorithms allow efficient real-time solutions for routing and swarm management.
The article examines the prospects of integrating quantum technologies into unmanned aerial vehicles (UAVs). Research on quantum technologies has been conducted in the development of new unmanned aircraft. Particular attention is given to quantum sensors for navigation, quantum optimization algorithms for autonomous control, and quantum key distribution (QKD) for secure communication. The research employs comparative analysis of classical and quantum sensors, a review of optimization algorithms (QAOA, VQE), and the principles of QKD. Laboratory and field test results are considered, along with the experience of international companies and startups. It is shown that quantum inertial sensors enable drift-free navigation even in “GPS-denied” environments. QKD ensures secure communication channels, while quantum optimization algorithms allow efficient real-time solutions for routing and swarm management.
Recent advances in small Unmanned Aerial System (sUAS) technologies lower the barriers for use by both private and commercial entities. However, these advances are also likely to lead to greater vehicle densities, a more heterogenous mix of vehicles and equipment and greater levels of vehicle autonomy, which can increase the chance for communications disruptions. For the safe and secure operation of these vehicles, it is essential to have a robust communications network. This work is focused on harnessing the power of quantum technologies to enable this robust communications network by: (1) utilizing quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents and (3) utilize quantum key distribution (QKD) to execute secure key sharing in anti-jamming protocols for secure radio frequency (RF) communication. Efforts to map these quantum optimization algorithms to commercially available quantum annealers and soon to be available general-purpose gate-model quantum hardware architectures will be reviewed, and plans for testing the solutions to these algorithms through indoor sUAS flight tests will be discussed. Lastly, efforts to miniaturize and practically deploy Quantum Key Distribution (QKD) hardware, which could ultimately be used to securely exchange encryption keys, in sUAS networks will be reviewed.
Secure communication is vital for unmanned aerial vehicle (UAV) operations, where ensuring data integrity and secrecy is essential. The distinctive challenges in UAV communication UAV communication and the evolving quantum computing field heighten the vulnerabilities of traditional cryptographic methods. Quantum cryptography quantum cryptography offers a promising solution by leveraging quantum mechanics to establish provably secure channels. This chapter provides a comprehensive overview of quantum cryptography quantum cryptography in UAV communications, covering fundamental concepts of quantum mechanics relevant to cryptography. It explores protocols like quantum key distribution (QKD QKD ), quantum secure direct communication (QSDC), and quantum teleportation, quantum teleportation discussing their applicability and limitations in UAV networks. Additionally, the chapter discusses how quantum communication can be effectively utilized for long-range UAV communication. Furthermore, it delves into implementing quantum cryptography-as-a-service for UAVs, presenting real-world case studies and outlining future directions and challenges. Serving as a roadmap for integrating quantum cryptography, this chapter ensures robust security in UAV operations against evolving threats.
Purpose of research . Modern unmanned aerial vehicles face challenges in maintaining reliable communications in the face of radio interference, difficult terrain (mountains, forests), or active electronic countermeasures. One possible solution to this problem is the application of quantum cryptography principles in combination with the latest communication protocols, such as LoRaWAN 2, which help ensure secure and stable data transmission in challenging environments. The Purpose of the esearch is to evaluate the feasibility of using quantum cryptography and the LoRaWAN 2 protocol to establish and maintain continuous, stable communication with an unmanned aerial vehicle. Methods . The research methods are based on concepts from statistical radio engineering theory and ultra-high-frequency radio wave propagation theory. Multicriteria analysis, parametric synthesis, and structural synthesis methods are used. The principles of information transmission from unmanned aerial vehicles are analyzed. A critical assessment of the performance of a UAV using quantum cryptography and the LoRaWAN 2 protocol is conducted. Results . Analytical expressions and comparative characteristics are presented to assess the potential for using quantum cryptography and the LoRaWAN 2 protocol with unmanned aerial vehicles. It is shown that using quantum cryptography, the probability of data interception in a UAV communication channel is approximately 1%, significantly increasing its security compared to RSA-2048. Quantum cryptography improves UAV security and key retrieval with a slight increase in weight, power consumption, and speed. In the coming years, with the development of compact systems, its promising implementation will become the standard for commercial drones. Conclusion . As promising areas of research and application in the field of using unmanned aerial vehicles, the use of quantum cryptography technology and the LoRaWAN 2 protocol should be considered, which contributes to improving the characteristics of UAVs: high range, energy efficiency, security and scalability.
Unmanned aerial vehicles (UAVs) have accordingly been successfully integrated into different industries, including military, healthcare, and education, because of their diverse applications and sophisticated capabilities. Nevertheless, UAVs are increasingly confronted with significant security and operational issues related to communications and collision avoidance. This chapter will discuss in detail the convergence of quantum cryptography with UAVs for enhanced security against these problems. Starting with a critical examination of the literature on the subject at hand, the paper traces the historical evolution of cryptography and discusses the present trends in UAV technology. The existing security standards are discussed, including their shortcomings, paving the way for the need for stricter ones. The principles of quantum cryptography, including quantum key distribution (QKD), are briefly summarized below in relation to classical cryptography. In the case of UAV communications, challenges include uniqueness threats, the real-time context, and the recently emerging problem of collision, all of which should be addressed. The proposed layered architecture here will include quantum cryptography to guarantee data security while enhancing communication efficiency. This will provide a framework for future development by explaining in detail the design, implementation, and security mechanisms of the proposed solution. Its performance will be evaluated in various case studies of military, healthcare, and education environments. The performance evaluation parameters have been addressed in detail to emphasize the strengths of the system and areas for improvement. The research raises the newly arising collision problem with UAVs and offers quantum solutions to improve the collision avoidance mechanism. This chapter will describe in depth how quantum cryptography merges with UAVs for increased protection against these issues. Beginning with a critical study of the available literature on the topic at hand, the paper follows the historical development of cryptography and discusses the current trends in UAVs. The prevailing security standards are discussed, along with their limitations, leading to the necessity for stricter ones. The quantum cryptographic principles, such as QKD, are briefly summarized below as applied to classical cryptography. Uniqueness threats, the real-time context, and the recently emerging problem of collision are challenges that should be addressed in the case of UAV communications.
The utilization of unmanned aerial vehicles (UAVs) in defense for functions, such as delivery and surveillance, has surged due to the fast progress of technology. UAV tracking and navigation system optimization is critical as UAV operations become more complicated. Quantum computing (QC) can significantly improve optimization procedures for real-time tracking, overcoming computational challenges and enhancing efficiency in UAV operations by handling large amounts of data. The study’s objective is to establish how QC performs in the optimization of UAV tracking. A novel Dynamic Kookaburra-tuned Malleable Convolutional Neural Network (DK-MCNN) is proposed to improve the tracking performance of UAVs. The data collected from video feeds from cameras mounted on UAVs, readings from GPS and other sensors outlining the specific paths and maneuvers the UAV will perform, ensuring diverse scenarios, including various terrains and environments. The data preprocessed using data cleaning and normalization involve removing erroneous or redundant data to ensure high-quality datasets. The study specifically focuses on leveraging QC into UAV tracking systems and promises to enhance performance, including speed, optimization, data handling and robustness. This technology has the potential to transform UAV operations, making them more efficient, reliable and capable of handling complex tasks in dynamic environments. The study evaluates the tracking accuracy, computational efficiency and resilience of the proposed method compared to traditional approaches across a range of operating situations. Extensive simulations of several tracking scenarios, encompassing urban, rural and disaster response situations, are employed to assess the efficacy of UAVs in monitoring and navigating across dynamic terrain. The outcomes illustrate the potential for real-time applications in UAV systems, by showing that the suggested technique dramatically decreases processing time and improves tracking accuracy, when compared to conventional algorithms.
Quantum computing is expected to mature in the coming years; however, traditional secure schemes, which might be used for computations and communications on unmanned aerial vehicles (UAVs), will need better solutions than simply updating passwords while disregarding specific systems like navigation or collision avoidance. In this paper, we propose an original method for improving the security of UAVs by embedding quantum-resistant cryptographic algorithms. Secure communication using lattice-based cryptography (Kyber) and message authentication using hash-based signatures (SPHINCS+) were selected based on the UAV hardware hierarchy for which these post-quantum systems are optimized. The developed system was tested in different flight conditions, including high-density UAV swarms, with the help of a simulation environment. The results show that secure communication between quantum-safe navigation and collision avoidance modules is possible with low latency, which does not cause a significant increase in computational cost or battery life consumption.