Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to p ....Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to provide these languages with improved memory-management algorithms, and provides researchers and industry with a framework for innovation. This project will enable safe software that is more efficient on today's hardware and able to exploit emerging hardware. This project should lead to better performance and energy savings for server applications, phones, watches, and smart appliances, while ensuring memory safety.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.Read moreRead less
Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutt ....Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a
warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This
project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutting-edge Blockchain based secure IoT data management and privacy-preserving smart contracts for smart farming supply-chain management. This data infrastructure will be the first of its kind which will lay a solid foundation for smart farming technology.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE240100131
Funder
Australian Research Council
Funding Amount
$539,000.00
Summary
Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boo ....Federated Omniverse Facilities for Smart Digital Futures. A world-first trans-disciplinary, -domain, and -institutional smart 3D omniverse R&D ecosystem AuVerse will be built in NSW, affiliated with Queensland, and accessible to academia and industry. AuVerse will support cloud-based, reality-virtuality-fused, immersive, interactive and secure future-oriented digital design, development, training and society. In the new era of digital innovation and paradigm shift, AuVerse will substantially boost Australia’s pivotal research leadership and business competitiveness in nurturing new-generation, collaborative and transformative digital R&D and talent pipeline. It will enable large-scale strategic business innovation and transformation including smart manufacturing and Industry 4.0.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100595
Funder
Australian Research Council
Funding Amount
$416,400.00
Summary
Efficient privacy-preserving proofs for secure e-government and e-voting. Electronic systems are becoming increasingly widespread and crucial to social and economic wellbeing. This project aims to ensure that e-government, e-health, e-commerce and e-voting are secure and trustworthy by inventing new ways to verify these systems without infringing privacy. This project expects to use innovative techniques from cryptography to support development of trustworthy systems. Expected outcomes of this p ....Efficient privacy-preserving proofs for secure e-government and e-voting. Electronic systems are becoming increasingly widespread and crucial to social and economic wellbeing. This project aims to ensure that e-government, e-health, e-commerce and e-voting are secure and trustworthy by inventing new ways to verify these systems without infringing privacy. This project expects to use innovative techniques from cryptography to support development of trustworthy systems. Expected outcomes of this project include better support for organisations to build trustworthy systems that will maximise benefit to Australian business and society. This should provide significant commercial, reputational, and societal benefits by avoiding disruptions to the organisations and their clients if and when they are attacked. Read moreRead less
Verified concurrent memory management on modern processors. This project aims to formally verify automatic memory managers in the presence of concurrency and the weakly ordered memory of modern processors. A new framework for verifying memory managers, reusable for a wide range of managed programming languages, target hardware, policies, and algorithms will be developed. Expected technical outcomes include improved techniques to ensure trustworthiness of the foundations on which critical softwar ....Verified concurrent memory management on modern processors. This project aims to formally verify automatic memory managers in the presence of concurrency and the weakly ordered memory of modern processors. A new framework for verifying memory managers, reusable for a wide range of managed programming languages, target hardware, policies, and algorithms will be developed. Expected technical outcomes include improved techniques to ensure trustworthiness of the foundations on which critical software infrastructures are built. This will significantly enhance the security of public and private cyber assets, and deliver applications that are more robust and trustworthy, across a range of critical infrastructure such as transportation, communication, energy and defence.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100672
Funder
Australian Research Council
Funding Amount
$470,337.00
Summary
Measuring real-time mental workload to improve our Defence capability. This project aims to develop a novel platform for measuring real-time variation in the cognitive workload of humans working with advanced Defence technologies. The project expects to combine innovative statistical techniques with cutting-edge psychological and neuroscience developments to measure and process workload-related brain activity in real-time. Expected outcomes of the project include an enhanced capacity to measure ....Measuring real-time mental workload to improve our Defence capability. This project aims to develop a novel platform for measuring real-time variation in the cognitive workload of humans working with advanced Defence technologies. The project expects to combine innovative statistical techniques with cutting-edge psychological and neuroscience developments to measure and process workload-related brain activity in real-time. Expected outcomes of the project include an enhanced capacity to measure and respond to cognitive workload in the field. This should provide significant benefits such as enhanced performance and safety outcomes, which will provide a strategic advantage to the Australian Defence Force by facilitating the development of advanced technologies that respond to the capabilities of the human user.Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less
Advanced materials for space propulsion: satellites and cubesats. Poorly controlled interactions between plasmas and surfaces often mean loss of process efficiency and surface degradation over time. For Hall thrusters, a type of engine used to move satellites in space, this means increased fuel consumption and shorter useful life. Through modelling and experiment, this project will show how intelligent selection of advanced materials and plasma parameters can minimise surface wear, enable in sit ....Advanced materials for space propulsion: satellites and cubesats. Poorly controlled interactions between plasmas and surfaces often mean loss of process efficiency and surface degradation over time. For Hall thrusters, a type of engine used to move satellites in space, this means increased fuel consumption and shorter useful life. Through modelling and experiment, this project will show how intelligent selection of advanced materials and plasma parameters can minimise surface wear, enable in situ material repair to extend device lifetime, and modulate plasma properties to increase thruster efficiency for a given task. These benefits enable reliable propulsion platforms for massive communication and observation satellite networks and deep space exploration.Read moreRead less