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布拉德福德大学招收网络安全博士

2023/7/26 10:57:23  阅读:41 发布者:

布拉德福德大学招收网络安全博士

About the Project

In beyond 5G and 6G communication networks, the need for robust security systems is paramount to securely store and share vast amounts of data globally. An essential aspect of network security lies in establishing secure communication of secret keys among trusted entities. In this regard, quantum key distribution (QKD) has been considered as a promising solution for achieving global security. By leveraging the principles of quantum physics, QKD enables authorized parties to share secret keys efficiently and regularly, thereby ensuring unconditional security [1].

To extend quantum communications globally, previous studies have explored various scenarios involving the use of free-space optical (FSO) links between ground stations and satellites, where satellites act as relaying nodes [2, 3]. However, the considerable distance between ground stations and satellites poses a significant challenge for reliable QKD. There is recently new concept of space-aerial-terrestrial integrated network (SATNet) [4]. Using SATNet and FSO links, we can go beyond the use of satellites alone and incorporates airborne platforms as relays for QKD. This quantum network (Q-SATNet) can improve the coverage and reliability of QKD. Nevertheless, key routing and resource allocation present significant challenges within this network. The dynamic nature of FSO channel, numerous QKD nodes, and movements of satellites and airborne platforms contribute to these challenges. While some studies have addressed networking issues in QKD networks, they have primarily focused on terrestrial fibre-based scenarios [5, 6]. Currently, there is still a lack of research addressing the issues of key routing and resource allocation in Q-SATNet.

The primary objective of this project is to address the existing research gap and contribute to the understanding and solutions for key routing and resource allocation in Q-SATNet. In the initial stage, comprehensive physical layer models will be developed, incorporating all relevant FSO channel impairments, and considering the effects of transceiver movements. Once these models are established, we will be able to simulate a dynamic Q-SATNet with multiple ground stations, satellites and airborne flatforms. Based on the Q-SATNet simulation, we will study intelligent networking techniques that can enhance the efficiency of key routing and resource allocation. This will potentially involve leveraging software-defined networking (SDN) and artificial intelligence (AI) techniques. For example, in terms of key routing, AI algorithms will be employed to dynamically adapt routing paths in response to changing network conditions, such as FSO link failures or network congestion. SDN will then be used in implementing these adaptive routing decisions by facilitating dynamic reconfiguration of QKD nodes. In resource allocation, SDN will provide a comprehensive view of network resources, including optical wavelengths and QKD nodes. By using AI techniques, the network controller will be able to analyse resource usage patterns, predict future demand, and dynamically allocate resources accordingly.

The research project will take place at the Bradford-Renduchintala Centre for Space AI, which is home to a team of experts specializing in FSO, satellite communications, SDN, and AI. These knowledgeable professionals will offer valuable assistance for the student involved in the project.

The project will involve utilizing methodologies related to communication channel modelling, network simulation, network management, cross-layer design and analysis. Applicants should have research experience or a strong willingness to develop knowledge and research skills in these areas. Students with a background in electrical and electronics engineering, telecommunications engineering, computer science, physics, or mathematics are particularly encouraged to apply.

How to apply

Formal applications can be made via the University of Bradford web site. Please select 'Full-time PhD in Electrical Engineering' as the course.

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