Trust monitoring framework in autonomous unmanned aerial systems

Keshavarz, Mahsa (2022) Trust monitoring framework in autonomous unmanned aerial systems. Doctoral thesis, Northern Arizona University.

Text KESHAVARZ_2022_trust_monitoring_framework_autonomous_unmanned_aerial_s.pdf - Published Version Restricted to Repository staff only Download (12MB) | Request a copy

Abstract

Multi-Agent Systems (MAS) refers to a system of several agents that interact to solve problems beyond each agent's individual capacities or knowledge. One example of MAS is unmanned aerial vehicles (UAVs). UAVs are widely used in several civilian and military operations, including remote sensing, surveillance, package delivery, disaster relief, and medical services. Due to their unique features, such as high mobility, ease of deployment, and ability to hover, UAVs can provide urgent Internet and communication services in time-critical missions or natural disasters. On the one hand, the UAVs are vulnerable to several attacks, including cyberattacks such as false data injection, physical attacks such as targeting the UAVs using firearms, and cyber-physical attacks such as GPS spoofing. On the other hand, in MASs, the agents need to rely on one another’s services and resources to perform their tasks. Any malicious behavior accordingly may lead to serious system breakdown in the long term. Therefore, developing robust trust monitoring mechanisms to identify potential attacks on these systems is crucial. The aim of this project is to develop a distributed trust management framework approach to solve this problem.

Item Type:	Thesis (Doctoral)
Publisher’s Statement:	© Copyright is held by the author. Digital access to this material is made possible by the Cline Library, Northern Arizona University. Further transmission, reproduction or presentation of protected items is prohibited except with permission of the author.
Additional Information:	Multi-agent systems; Unmanned aerial vehicles; System vulerabilities; System breakdown
Subjects:	T Technology > TJ Mechanical engineering and machinery
NAU Depositing Author Academic Status:	Student
Department/Unit:	Graduate College > Theses and Dissertations College of Engineering, Informatics, and Applied Sciences > School of Informatics, Computing, and Cyber Systems
Date Deposited:	12 Jun 2023 17:50
Last Modified:	12 Jun 2023 17:50
URI:	https://openknowledge.nau.edu/id/eprint/6001

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