Resilient architecture to dynamically manage unmanned aerial vehicle networks under attack

• Ano de defesa: 2021
• Autor(a) principal: Ferrão, Isadora Garcia
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Arquitetura Resiliente; Decision making; Proteção; Resilient architecture; Safety; Security; Segurança; Tomada de decisão; Unmanned aerial vehicle; Veículo Aéreo Não Tripulado
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-23062021-125834/

There is a growing demand for unmanned aerial vehicles (UAV) in the industry since they are being used on a large scale in various fields, such as health, security, military missions, agriculture, etc. These vehicles have the potential to increase productivity and savings. However, the increase in production and use of unmanned aerial vehicles requires improving sound decision-making principles, physical, computational security, and relevant technologies by the computing community. They must continually adapt to carry out missions where they face unpredictable problems. The increase in advanced functionality and the demand for computing capacity exposes these vehicles to different security vulnerabilities. These vulnerabilities are growing not only in number but also in sophistication. Researchers and companies have been developing multidisciplinary methodologies and approaches in recent years, trying to solve the most varied protection and safety problems around unmanned aerial vehicles. As in the past, concerns about unmanned aerial vehicles safety were with aggressors and hijackers, now with the domain of civilian application and insertion into the network, circumstances have changed. In this context, this dissertations objective was to advance state-of-the-art through the definition and development of a resilient architecture for unmanned aerial vehicles (STUART - reSilient archiTecture to dynamically manage Unmanned aeriAl vehicle networksundeR atTack) that dynamically manages the network, even when subjected to an attack during a mission, integrating safety and security methods. The architecture is composed of four parts: (1) Anomaly-based detection system, (2) Triage module, (3) Decision-making module, and (4) Resilience module. This dissertation also investigated the incorporation of safety and security as a unified concept in UAV development. The developed architecture was validated by applying specific techniques in each of the parts that compose the architecture. Three tests were performed: one with a real drone and two tests using computer simulation, composed of a base station and a UAV during a vaccine transport mission for COVID-19. The results allow us to conclude that STUART is effective in detecting GPS spoofing. Unlike other architectures found in the literature that focus on specific missions or vulnerabilities, STUART proposes an organizational structure of metrics aggregated for different contexts, ranging from vulnerability detection, filtering false positives, decision-making, and mitigation. Its efficiency has been proven through computational validation using real data from a drone.