Harnessing innate immunity to mitigate bovine respiratory disease. Bovine Respiratory Disease (BRD) is the most significant health problem faced by the beef industry worldwide, causing economic losses of up to $40 million annually in Australia alone. This Project aims to assess an immunostimulant for its ability to induce resistance to infection with bovine respiratory viruses associated with BRD. The Project is expected to generate fundamental new knowledge in veterinary virology. Expected outc ....Harnessing innate immunity to mitigate bovine respiratory disease. Bovine Respiratory Disease (BRD) is the most significant health problem faced by the beef industry worldwide, causing economic losses of up to $40 million annually in Australia alone. This Project aims to assess an immunostimulant for its ability to induce resistance to infection with bovine respiratory viruses associated with BRD. The Project is expected to generate fundamental new knowledge in veterinary virology. Expected outcomes include scholarly publications. The Project will provide significant benefits, such as advances to fundamental knowledge, training of higher research degree students and proof-of-concept data to promote collaborations with commercial partners to develop novel treatment strategies to limit BRD.Read moreRead less
Deep Learning Attacks and Active Defences: A Cybersecurity Perspective. The belief that deep learning technology is imperative for economic development, military control, and strategic competitiveness has accelerated its development across the globe. However, experience has revealed the disappointing fact that deep learning models are vulnerable to a range of security attacks. Hence, a series of methodologies and defence strategies will be devised that make deep learning systems robust to these ....Deep Learning Attacks and Active Defences: A Cybersecurity Perspective. The belief that deep learning technology is imperative for economic development, military control, and strategic competitiveness has accelerated its development across the globe. However, experience has revealed the disappointing fact that deep learning models are vulnerable to a range of security attacks. Hence, a series of methodologies and defence strategies will be devised that make deep learning systems robust to these attacks. The methodologies require analysing attack lifecycles to identify them in their early stages. With this knowledge, active defence methods and forensic strategies can be developed to ensure efficient defences and prevent further attacks. Moreover, the outputs will be generalisable to most deep learning services.Read moreRead less
Non-urban water governance: rethinking compliance and enforcement. This project aims to critically evaluate the practices and strategies of non-urban water compliance and enforcement in Australia and internationally, to identify and develop innovations for water governance. New law and policy knowledge is expected from its fusion of empirical data and regulatory theory. The project expects to advance applied regulatory theory by identifying improvements in compliance and enforcement to help solv ....Non-urban water governance: rethinking compliance and enforcement. This project aims to critically evaluate the practices and strategies of non-urban water compliance and enforcement in Australia and internationally, to identify and develop innovations for water governance. New law and policy knowledge is expected from its fusion of empirical data and regulatory theory. The project expects to advance applied regulatory theory by identifying improvements in compliance and enforcement to help solve environmental issues. It will also lead to policy reforms for delivering more effective, efficient and politically-acceptable compliance outcomes for non-urban water management that will benefit water regulators and the sustainability and productivity of Australia's agricultural industry.Read moreRead less
Balance and reinforcement: privacy and fairness in high intelligence models. The aim of this project is to develop a series of privacy preservation methods to achieve a new balance between privacy and fairness in highly accurate intelligence models. The main issue in achieving this goal is that high-accuracy intelligence technologies have resulted in significant privacy violations and are very vulnerable to issues of unfairness. This project will analyse the privacy risks associated with intelli ....Balance and reinforcement: privacy and fairness in high intelligence models. The aim of this project is to develop a series of privacy preservation methods to achieve a new balance between privacy and fairness in highly accurate intelligence models. The main issue in achieving this goal is that high-accuracy intelligence technologies have resulted in significant privacy violations and are very vulnerable to issues of unfairness. This project will analyse the privacy risks associated with intelligent systems and devise mechanisms to mutually reinforce both privacy and fairness based on the theoretical foundations laid by our analysis. These outcomes will enable model owners to effectively protect their intellectual property and offer services to users in a private, fair, and accurate manner.Read moreRead less
Reverse chemical proteomics: harnessing yeast display for drug discovery. This project aims to develop a technique that can rapidly identify the cellular protein targets of biologically active natural products. This project expects to provide fundamental biological and chemical insights into Australia's unique biodiversity that will facilitate the development of new therapeutic agents and agrochemicals based on leads provided by Nature. Expected outcomes of this project include an optimised and ....Reverse chemical proteomics: harnessing yeast display for drug discovery. This project aims to develop a technique that can rapidly identify the cellular protein targets of biologically active natural products. This project expects to provide fundamental biological and chemical insights into Australia's unique biodiversity that will facilitate the development of new therapeutic agents and agrochemicals based on leads provided by Nature. Expected outcomes of this project include an optimised and validated platform technology for accelerating drug discovery and development. This should substantially reduce the costs associated with fighting human and animal diseases, leading to improved health, productivity and quality of life.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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Imperfect vaccination drives herpesvirus evolution through recombination. Vaccines are used to help control disease caused by herpesviruses in animals, but some vaccination programs may drive the evolution and spread of herpesviruses with increased fitness (transmissibility, replication and virulence) through recombination. This project aims to study an important avian herpesvirus (infectious laryngotracheitis virus) in the natural host (poultry) to gain fundamental knowledge of how vaccination ....Imperfect vaccination drives herpesvirus evolution through recombination. Vaccines are used to help control disease caused by herpesviruses in animals, but some vaccination programs may drive the evolution and spread of herpesviruses with increased fitness (transmissibility, replication and virulence) through recombination. This project aims to study an important avian herpesvirus (infectious laryngotracheitis virus) in the natural host (poultry) to gain fundamental knowledge of how vaccination programs influence the emergence of diverse recombinant viruses, and identify which types of vaccination programs are best at preventing the emergence of fitter and more virulent viruses. The results are expected to inform vaccination practices to allow more effective control of these viruses in poultry and other animals.Read moreRead less
A peptide platform to fight pests threatening global food security. This project aims to develop a platform technology for the efficient design of new crop protection agents based on peptides to protect Australia’s food security. It will be first applied against the highly destructive fall armyworm, currently spreading alarmingly in Australia. The project is significant because insect pests cause huge economic and environmental impacts. Peptides are a new generation of crop protection agents tha ....A peptide platform to fight pests threatening global food security. This project aims to develop a platform technology for the efficient design of new crop protection agents based on peptides to protect Australia’s food security. It will be first applied against the highly destructive fall armyworm, currently spreading alarmingly in Australia. The project is significant because insect pests cause huge economic and environmental impacts. Peptides are a new generation of crop protection agents that are potentially more effective and sustainable than chemical pesticides. Expected outcomes are a new rapid response technology and associated lead molecules to protect against current and emerging pests. Major benefits are increased food security, improved crop yields and a more sustainable agriculture industry. Read moreRead less
Efficient and secure data integrity auditing on cloud. Data auditing presents a promising way for verifying user data integrity on cloud, i.e., whether user privacy sensitive data such as identity information on cloud is modified or lost. Current auditing approaches lack sufficient efficiency and security. This results in that they cannot provide timely warning and precaution on potential data loss threats. This project aims to systematically investigate this significant challenge and expects to ....Efficient and secure data integrity auditing on cloud. Data auditing presents a promising way for verifying user data integrity on cloud, i.e., whether user privacy sensitive data such as identity information on cloud is modified or lost. Current auditing approaches lack sufficient efficiency and security. This results in that they cannot provide timely warning and precaution on potential data loss threats. This project aims to systematically investigate this significant challenge and expects to establish innovative research and solutions for enabling efficient and secure data integrity auditing on cloud. The project outcomes will help to safeguard Australian community in fast-growing cyber world, and benefit to fast-growing user privacy sensitive data hosting and applications on cloud.Read moreRead less
Attribution of Machine-generated Code for Accountability. Machine-generated (or neural) code is usually produced by AI tools to speed up software development. However, such codes have recently raised serious security and privacy concerns. This project aims to attribute these codes to their generative models for accountability purposes. In the process, a series of new techniques are developed to differentiate between the codes generated by different models. The outcomes include analysis of neural ....Attribution of Machine-generated Code for Accountability. Machine-generated (or neural) code is usually produced by AI tools to speed up software development. However, such codes have recently raised serious security and privacy concerns. This project aims to attribute these codes to their generative models for accountability purposes. In the process, a series of new techniques are developed to differentiate between the codes generated by different models. The outcomes include analysis of neural code fingerprints, classification of neural codes, and theories to verify the correctness of code attribution. These will provide significant benefits, ranging from copyright protection to privacy preservation. This project is timely since currently the software community is pervasively using neural codes.Read moreRead less