Secure Identity Management System in Unmanned Aerial Vehicles Network

In recent years, rapid advancements in digital transformation and communication technologies have led to the widespread adoption of autonomous systems, particularly Unmanned Aerial Vehicles (UAVs), in societal and industrial applications. The integration of smart cities, the Internet of Things (IoT), and 5G technologies has enabled UAVs to be utilized effectively in more complex and dynamic tasks. For instance, during the COVID-19 pandemic, UAVs played critical roles in maintaining social distancing, delivering medical supplies, and managing crowds. Such contemporary applications have once again highlighted the importance and potential of UAV networks. The flexibility and versatility offered by UAVs facilitate the development of innovative solutions across a wide spectrum—from agriculture to logistics, disaster management to security. Specifically, swarm UAV systems surpass the limitations of individual vehicles, providing advantages such as real-time data collection, large-scale monitoring, and the parallel execution of complex tasks. However, the effective and secure operation of such systems depends on the reliability and efficiency of intra-network communication and identity management protocols. In today's cyber-physical systems, security threats and cyber-attacks are becoming increasingly sophisticated. UAV networks are not exempt from these threats; risks such as identity spoofing, data manipulation, and Denial-of-Service (DoS) attacks endanger the success and security of operations. Addressing these security vulnerabilities is of vital importance, especially in sensitive areas like the protection of critical infrastructures, border security, and emergency interventions. This thesis aims to enhance the operational efficiency and security of UAV networks by developing a lightweight and dynamic identity management protocol alongside a consensus mechanism specifically optimized for UAV networks. The proposed identity management protocol employs symmetric cryptography and hash functions, featuring low computational and communication overhead while adapting to dynamic network topologies. The protocol is resilient against common security threats such as identity spoofing, replay attacks, and man-in-the-middle attacks. Furthermore, leveraging the advantages of blockchain technology, a fast and efficient consensus mechanism suitable for UAV networks has been designed. Instead of energy-intensive and high-latency methods like traditional Proof of Work (PoW), an adapted version of the Practical Byzantine Fault Tolerance (PBFT) algorithm and a Fuzzy C-Means Clustering algorithm (FCMCA) are utilized to reduce latency and computational costs. This mechanism enables secure and effective data sharing and decision-making processes among UAVs. Simulations and performance analyses have demonstrated that the proposed solutions provide lower latency and reduced resource consumption compared to existing methods, while exhibiting high resilience against security threats. These findings contribute significantly to the safer, more efficient, and scalable use of UAV networks in real-world applications. The study aims to establish a solid foundation for the evolution and sustainability of UAV networks and serves as a valuable reference for future technological developments and applications.