Robust Defences against Adversarial Machine Learning for UAV Systems

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This project aims to investigate robust defences for Unmanned Aerial Vehicle (UAV) systems to protect them against adversarial Machine Learning (ML) attacks. This project expects to generate new knowledge in the area of cybersecurity using innovative approaches to safeguard UAV systems from attacks that exploit vulnerabilities in ML models. The expected outcomes of this project include improve techniques for understanding and developing robust ML models and enhanced capacity to design secure UAV systems. This should provide significant benefits, such as improving the security of UAV technology and increasing the reliable use of UAVs for transport and logistics services to support urban and regional communities in Australia.