Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.Read moreRead less
Next generation high throughput lipidomics using adaptive modelling. This project aims to develop a unique high-throughput method to capture the lipidomic profile of human plasma suitable for large human population screening. Lipids are fundamental to every biological system, but our understanding of their regulation in humans have been largely superficial. By incorporating a new lipidomics approach, with genomic data, this project aims to expand our understanding of human biology by identifying ....Next generation high throughput lipidomics using adaptive modelling. This project aims to develop a unique high-throughput method to capture the lipidomic profile of human plasma suitable for large human population screening. Lipids are fundamental to every biological system, but our understanding of their regulation in humans have been largely superficial. By incorporating a new lipidomics approach, with genomic data, this project aims to expand our understanding of human biology by identifying regulators of lipid metabolism. The large diversity in humans necessitate sufficient sample sizes to identify true genetic regulators, but to date techniques capturing phenotypic data (lipids) have been largely limited. It is anticipated that this study will identify new regulators of lipid metabolism in humans.Read moreRead less
Accelerating pulse breeding using machine learning. Advances in genomics and high throughput phenotyping are generating vast quantities of data that can be applied for crop improvement, however the lack of computational analysis tools and approaches limits the full exploitation of this data. Pulse legumes are currently under utilised in Australian agriculture due to poor adaptation, however they offer significant benefits both for soil improvement and the production of high protein crops. This p ....Accelerating pulse breeding using machine learning. Advances in genomics and high throughput phenotyping are generating vast quantities of data that can be applied for crop improvement, however the lack of computational analysis tools and approaches limits the full exploitation of this data. Pulse legumes are currently under utilised in Australian agriculture due to poor adaptation, however they offer significant benefits both for soil improvement and the production of high protein crops. This project will develop machine learning (ML) tools for the analysis of pulse legume crop traits and their association with genomic variation to accelerate the breeding of high performance pulse legumes for Australian growers.Read moreRead less
Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptiv ....Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptive trust and integrity preserving methods, and reliable distributed data processing mechanisms to mitigate vulnerabilities in real-time IoT-enabled critical surveillance. This should provide significant benefits to Australia's economy, one of which is the enhanced consumer-centric adoption of IoT for sensitive operations.Read moreRead less
Who’s who in the plant gene world? As many more plant genomes are sequenced, the bottleneck is being able to interrogate and translate this data into applications for crop improvement. This project will develop and apply a population graph database, hosting genome data for the world’s major crops and their wild relatives, allowing the characterisation of gene diversity on an unparalleled scale. Analysis of this data will reveal the presence/absence and sequence diversity for classes of genes for ....Who’s who in the plant gene world? As many more plant genomes are sequenced, the bottleneck is being able to interrogate and translate this data into applications for crop improvement. This project will develop and apply a population graph database, hosting genome data for the world’s major crops and their wild relatives, allowing the characterisation of gene diversity on an unparalleled scale. Analysis of this data will reveal the presence/absence and sequence diversity for classes of genes for important agronomic traits including disease resistance, flowering time and legume nitrogen fixation which will enable plant breeders to identify and apply novel genes and allelic variants for use in breeding programmes, accelerating the production of improved crop varieties.Read moreRead less
IDENTIFYING CONTROL ELEMENTS IN CHLOROPLAST GENE EXPRESSION. Energy from sunlight is captured by photosynthesis in plants, providing the basis for the terrestrial food chain. This process takes place in chloroplasts, subcellular structures that derived from photosynthetic bacteria a billion years ago. Chloroplasts have their own DNA, containing genes encoding the most important photosynthetic proteins. This project aims to provide the world’s best resources for the study of chloroplast genes. In ....IDENTIFYING CONTROL ELEMENTS IN CHLOROPLAST GENE EXPRESSION. Energy from sunlight is captured by photosynthesis in plants, providing the basis for the terrestrial food chain. This process takes place in chloroplasts, subcellular structures that derived from photosynthetic bacteria a billion years ago. Chloroplasts have their own DNA, containing genes encoding the most important photosynthetic proteins. This project aims to provide the world’s best resources for the study of chloroplast genes. In the process, we will discover how these important genes are regulated to provide photosynthetic proteins in the right amounts, in the right cells, at the right time. The knowledge and resources gained will facilitate improvement of photosynthetic function in future agricultural crops.Read moreRead less
The adaptive evolution of key methane-utilising microorganisms. This project aims to characterise the evolutionary adaptations of a group of microorganisms with a key role in mitigating the release of methane into the atmosphere. Innovative molecular and visualisation-based approaches will be applied to uncover their metabolic diversity and evolutionary history. An important outcome of this study will be the comprehensive understanding of the contribution and impact these microorganisms have on ....The adaptive evolution of key methane-utilising microorganisms. This project aims to characterise the evolutionary adaptations of a group of microorganisms with a key role in mitigating the release of methane into the atmosphere. Innovative molecular and visualisation-based approaches will be applied to uncover their metabolic diversity and evolutionary history. An important outcome of this study will be the comprehensive understanding of the contribution and impact these microorganisms have on the global carbon cycle, which will importantly inform accurate climate change models. This has clear benefits for society, given the precision of such models is essential in our ability to minimise the impact and associated cost of global warming.Read moreRead less
Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods an ....Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods and efficient algorithms that will be able to prevent real-time exfiltration and identify previously undetected exfiltration of sensitive data. This should provide significant benefits to governments, defence networks as well as businesses and health sectors, as it will protect them from sophisticated cyber attacks.
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