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Secure Identity Management System in Unmanned Aerial Vehicles Network / HULYA DOGAN

Swansea University Author: HULYA DOGAN

DOI (Published version): 10.23889/SUThesis.70396

Abstract

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)...

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Published: Swansea University, Wales, UK 2025
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
Supervisor: Setzer, A.
URI: https://cronfa.swan.ac.uk/Record/cronfa70396
first_indexed 2025-09-18T12:15:10Z
last_indexed 2025-09-19T14:52:51Z
id cronfa70396
recordtype RisThesis
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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&#x2014;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.</abstract><type>E-Thesis</type><journal/><volume/><journalNumber/><paginationStart/><paginationEnd/><publisher/><placeOfPublication>Swansea University, Wales, UK</placeOfPublication><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic/><keywords>Unmanned Aerial Vehicles (UAVs), UAV Networks, Identity Management System, Consensus Protocol, Blockchain, Practical Byzantine Fault Tolerance (PBFT), Fuzzy C-Means Clustering Algorithm (FCMCA),Swarm UAV Systems, Symmetric Cryptography, Cyber-physical Systems, Security Threats, Dynamic Network Topologies</keywords><publishedDay>4</publishedDay><publishedMonth>8</publishedMonth><publishedYear>2025</publishedYear><publishedDate>2025-08-04</publishedDate><doi>10.23889/SUThesis.70396</doi><url/><notes>A selection of content is redacted or is partially redacted from this thesis to protect sensitive and personal information.</notes><college>COLLEGE NANME</college><CollegeCode>COLLEGE CODE</CollegeCode><institution>Swansea University</institution><supervisor>Setzer, A.</supervisor><degreelevel>Doctoral</degreelevel><degreename>Ph.D</degreename><degreesponsorsfunders>Turkish ministry of national education</degreesponsorsfunders><apcterm/><funders>Turkish ministry of national education</funders><projectreference/><lastEdited>2025-09-18T13:24:57.5372770</lastEdited><Created>2025-09-18T13:05:14.7787896</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>HULYA</firstname><surname>DOGAN</surname><order>1</order></author></authors><documents><document><filename>70396__35129__efc25915a29a4e758bcd38a9dff60fe1.pdf</filename><originalFilename>2024_Dogan_H.final.70396.pdf</originalFilename><uploaded>2025-09-18T13:14:48.0456807</uploaded><type>Output</type><contentLength>3911613</contentLength><contentType>application/pdf</contentType><version>E-Thesis &#x2013; open access</version><cronfaStatus>true</cronfaStatus><documentNotes>Copyright: The author, Hulya Dogan, 2024</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
spelling 2025-09-18T13:24:57.5372770 v2 70396 2025-09-18 Secure Identity Management System in Unmanned Aerial Vehicles Network 2eed697d82a6b057f2f713d2f3c61abd HULYA DOGAN HULYA DOGAN true false 2025-09-18 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. E-Thesis Swansea University, Wales, UK Unmanned Aerial Vehicles (UAVs), UAV Networks, Identity Management System, Consensus Protocol, Blockchain, Practical Byzantine Fault Tolerance (PBFT), Fuzzy C-Means Clustering Algorithm (FCMCA),Swarm UAV Systems, Symmetric Cryptography, Cyber-physical Systems, Security Threats, Dynamic Network Topologies 4 8 2025 2025-08-04 10.23889/SUThesis.70396 A selection of content is redacted or is partially redacted from this thesis to protect sensitive and personal information. COLLEGE NANME COLLEGE CODE Swansea University Setzer, A. Doctoral Ph.D Turkish ministry of national education Turkish ministry of national education 2025-09-18T13:24:57.5372770 2025-09-18T13:05:14.7787896 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science HULYA DOGAN 1 70396__35129__efc25915a29a4e758bcd38a9dff60fe1.pdf 2024_Dogan_H.final.70396.pdf 2025-09-18T13:14:48.0456807 Output 3911613 application/pdf E-Thesis – open access true Copyright: The author, Hulya Dogan, 2024 true eng
title Secure Identity Management System in Unmanned Aerial Vehicles Network
spellingShingle Secure Identity Management System in Unmanned Aerial Vehicles Network
HULYA DOGAN
title_short Secure Identity Management System in Unmanned Aerial Vehicles Network
title_full Secure Identity Management System in Unmanned Aerial Vehicles Network
title_fullStr Secure Identity Management System in Unmanned Aerial Vehicles Network
title_full_unstemmed Secure Identity Management System in Unmanned Aerial Vehicles Network
title_sort Secure Identity Management System in Unmanned Aerial Vehicles Network
author_id_str_mv 2eed697d82a6b057f2f713d2f3c61abd
author_id_fullname_str_mv 2eed697d82a6b057f2f713d2f3c61abd_***_HULYA DOGAN
author HULYA DOGAN
author2 HULYA DOGAN
format E-Thesis
publishDate 2025
institution Swansea University
doi_str_mv 10.23889/SUThesis.70396
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description 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.
published_date 2025-08-04T05:26:01Z
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score 11.089572

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