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
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
Privacy, Data Protection and Market Structure. The rise of the digital economy has led to an unprecedented scale of data collection, storage and processing, creating new privacy risks for individuals. This project will provide an economic analysis of the incentives and institutions necessary to ensure data is sufficiently protected while also providing adequate levels of privacy to individuals. It will do this by exploring the optimal design of privacy laws, data breach notification laws, and th ....Privacy, Data Protection and Market Structure. The rise of the digital economy has led to an unprecedented scale of data collection, storage and processing, creating new privacy risks for individuals. This project will provide an economic analysis of the incentives and institutions necessary to ensure data is sufficiently protected while also providing adequate levels of privacy to individuals. It will do this by exploring the optimal design of privacy laws, data breach notification laws, and the relationship between promoting competition and encouraging data protection investment. The outcomes of this research will contribute to the efforts of the federal government to build a secure and resilient digital infrastructure that supports the entire Australian knowledge economy.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100477
Funder
Australian Research Council
Funding Amount
$421,554.00
Summary
Advancing Human Perception: Countering Evolving Malicious Fake Visual Data. The aim of this project is to provide new effective and generalisable deepfake detection methods for automatically detecting maliciously manipulated visual data generated by misused artificial intelligence (AI) techniques. It will present innovative computer vision and image processing knowledge and techniques, enabling the developed methods to advance human perception in recognising fake data, enhance cybersecurity, and ....Advancing Human Perception: Countering Evolving Malicious Fake Visual Data. The aim of this project is to provide new effective and generalisable deepfake detection methods for automatically detecting maliciously manipulated visual data generated by misused artificial intelligence (AI) techniques. It will present innovative computer vision and image processing knowledge and techniques, enabling the developed methods to advance human perception in recognising fake data, enhance cybersecurity, and protect privacy in AI applications. The anticipated outcomes should provide significant benefits to a wide range of applications, such as providing timely alerts to the media, government organisations, and the industry about misleading fake visual data, and preventing financial crimes on synthetic identity fraud.Read moreRead less
Securing Web-based Services by Policy Coherence and Proof-checking. This project aims to develop a provably correct cybersecurity system for workflows, which enables organizations to provide flexible and more secure web-based services and business communication. The project expects to generate new knowledge, theoretic advancement and result in new technologies in the areas of internet of things and cybersecurity. The expected outcomes include a software tool with documentation, which helps organ ....Securing Web-based Services by Policy Coherence and Proof-checking. This project aims to develop a provably correct cybersecurity system for workflows, which enables organizations to provide flexible and more secure web-based services and business communication. The project expects to generate new knowledge, theoretic advancement and result in new technologies in the areas of internet of things and cybersecurity. The expected outcomes include a software tool with documentation, which helps organisations achieve operational excellence and security, and maintain a trusted environment for end users. This system will provide significant economic and commercial benefits to business and end users with highly secured web-services and improved productivity through a coherent framework and proof-checked workflows.Read moreRead less
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