Responsible modelling respecting privacy, data quality, and green computing. With the unprecedented growing impact of data on science, the economy and society, there comes the need for responsible data science practices which are accountable for the social good. This project aims to investigate the challenging problem of how to provide responsible data management, spanning across privacy-aware data exploration, resilient modelling to cope with imperfect data, and efficient model architectures fo ....Responsible modelling respecting privacy, data quality, and green computing. With the unprecedented growing impact of data on science, the economy and society, there comes the need for responsible data science practices which are accountable for the social good. This project aims to investigate the challenging problem of how to provide responsible data management, spanning across privacy-aware data exploration, resilient modelling to cope with imperfect data, and efficient model architectures for resource-constrained environments. This will be achieved by developing theories and techniques for complex real-world multi-modal data retrieval throughout the data life-cycle. The expected outcomes will significantly contribute to building capability in emerging technologies in the context of responsible data science. Read moreRead less
Rigorous Privacy Compliance in Modern Application Ecosystems. Modern network applications such as mobile applications and browser extensions have become the primary gateways for consumers to access the Internet in today’s digital landscape. This project aims to address privacy issues in these ecosystems by developing a new privacy-compliance assessment framework. The framework will evaluate the current privacy practices of application ecosystems, enabling users and developers in Australia and wo ....Rigorous Privacy Compliance in Modern Application Ecosystems. Modern network applications such as mobile applications and browser extensions have become the primary gateways for consumers to access the Internet in today’s digital landscape. This project aims to address privacy issues in these ecosystems by developing a new privacy-compliance assessment framework. The framework will evaluate the current privacy practices of application ecosystems, enabling users and developers in Australia and worldwide to reliably identify potential privacy risks and issues on their applications. The intended outcomes should endow data controllers with the capability of evidencing their compliance of data protection legislations such as Australia Privacy Act 1988 and EU General Data Protection Regulation (GDPR).Read moreRead less
Robust Defences against Adversarial Machine Learning for UAV Systems. 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 ....Robust Defences against Adversarial Machine Learning for UAV Systems. 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.Read moreRead less