Single Shot X-ray Tomography For Real-Time Functional X-ray Imaging
Funder
National Health and Medical Research Council
Funding Amount
$322,641.00
Summary
Computed Tomography (CT) scanners produce three-dimensional images of vital organs that cannot be obtained by conventional two-dimensional (single projection) x-ray radiographs. However, the radiation exposure is hundreds of times higher than conventional radiography. We will develop the world’s first CT scanner that uses no more radiation than a single conventional x-ray image that will provide four-dimensional reconstructions of a patient’s moving internal organs.
Developing Interpretable Machine Learning Models For Clinical Imaging And Single-cell Genomics
Funder
National Health and Medical Research Council
Funding Amount
$1,312,250.00
Summary
Machine learning methods will be vital to make best use of the deluge of data generated by high-throughput technologies in biomedical science. To get the most out of these models, however, we need to be able to unpack the 'black box'. I will use curated clinical and public research data to benchmark and develop interpretable deep learning models and software tools. These models will be used for breast cancer screening programs and for analysis of complex, large-scale single-cell genomics data.
Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a unive ....Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a universal data structure, which unfortunately makes it hard to separate trusted code from untrusted user-provided data. This project intends to develop novel program analysis tools and string constraint solvers, and employ these tools to support sophisticated automated reasoning about string manipulating software.Read moreRead less
From The Synchrotron To The Clinic: Translation Of A Novel Functional Lung Imaging Technology
Funder
National Health and Medical Research Council
Funding Amount
$891,834.00
Summary
Our team has recently developed a synchrotron technology with a startling capacity for dynamic functional imaging that can act as a sensitive regional indicator of lung disease. We will demonstrate that this technology can be translated from the synchrotron to the lab and eventually the clinic. We will provide proof of this concept by the application of this technology to emphysema, asthma, lung cancer, cystic fibrosis lung disease and neonatal resuscitation.
Imaging Neutrophil And Endothelial Function In Acute Glomerulonephritis
Funder
National Health and Medical Research Council
Funding Amount
$545,517.00
Summary
The glomerulus is a group of small blood vessels which form the filtering component of the kidney. In many diseases, it can be the target of an inappropriate inflammatory response during which white blood cells accumulate in the glomerular blood vessels and cause damage. In this project, we will visualise the blood vessel lining of the glomerulus in order to understand how white blood cells damage this region and cause leakage of protein leak into the urine.
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
Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not o ....Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not only practical solutions for protecting sensitive data recorded in blockchain but also crucial techniques to make the blockchain accountable for practical applications with enhanced security. This project provides significant benefits, such as building a trusted environment for sensitive transactions in the digital economy.Read moreRead less
Domain-specific visual languages for big data analytics applications. This project aims to invent domain-specific visual languages and support model-driven engineering based infrastructure so domain experts can specify, generate and apply complex data analytics and visualisation techniques. Many domains, including intelligent transport, business intelligence, and population health, need more effective “big data” analytics and visualisation. A challenge is to combine detailed domain knowledge – w ....Domain-specific visual languages for big data analytics applications. This project aims to invent domain-specific visual languages and support model-driven engineering based infrastructure so domain experts can specify, generate and apply complex data analytics and visualisation techniques. Many domains, including intelligent transport, business intelligence, and population health, need more effective “big data” analytics and visualisation. A challenge is to combine detailed domain knowledge – what the data means and what it can be used for – with sophisticated, scalable computational techniques to mine and present information from the huge volumes of raw data. This project is expected to improve productivity and quality of big data analytics and visualisation in critical domains.Read moreRead less
Preventing sensitive data exfiltration from insiders . Confidential data such as military secrets or intellectual property must never be disclosed outside the organisation; formally protecting data exfiltration from insider attacks is a major challenge. This project aims to develop a pattern matching based systematic methodology for data exfiltration in database systems. We will devise highly accurate detection tools and secure provenance techniques that can effectively protect against insider a ....Preventing sensitive data exfiltration from insiders . Confidential data such as military secrets or intellectual property must never be disclosed outside the organisation; formally protecting data exfiltration from insider attacks is a major challenge. This project aims to develop a pattern matching based systematic methodology for data exfiltration in database systems. We will devise highly accurate detection tools and secure provenance techniques that can effectively protect against insider attacks. The outcomes of the project will incorporate new security constraints and policies raised by emerging technologies to enable better protection of sensitive information. Read moreRead less