Detecting Supervisory Control and Data Access (SCADA) malicious programs to protect Australian critical infrastructure. The security of SCADA systems has enormous impact to our national security and economy because they control and monitor critical infrastructure, like power, gas and water facilities and nuclear power plants, etc. This project aims to investigate the security issues and provide innovative technological solutions to detect and prevent such problems.
Discovery Early Career Researcher Award - Grant ID: DE130100771
Funder
Australian Research Council
Funding Amount
$278,780.00
Summary
Automated system for bone texture analysis of osteoarthritis in hand radiographs. Early detection and prediction of hand osteoarthritis are not feasible by current methods of visual grading of hand radiographs. This project will develop a novel, fully automated system for selection of bone texture regions on hand radiographs and their analysis to address this problem.
Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor ....Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor authentication performance, which is not commercially applicable. This project aims to investigate innovative solutions to this issue. The intended deliverables will include deep learning based biometric feature extractor, cancellable biometrics and cloud oriented biometrics security protocols. Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE110100049
Funder
Australian Research Council
Funding Amount
$600,000.00
Summary
Establishment of the Australian data archive: an integrated research facility for the social sciences and humanities. The Australian data archive will enable Australia's leading researchers to address complex social, economic and environmental problems, leading to the development of evidence based policy. The archive will have an open access policy which will ensure that the general public, media and government and non-government agencies are able to examine the data used by researchers to arriv ....Establishment of the Australian data archive: an integrated research facility for the social sciences and humanities. The Australian data archive will enable Australia's leading researchers to address complex social, economic and environmental problems, leading to the development of evidence based policy. The archive will have an open access policy which will ensure that the general public, media and government and non-government agencies are able to examine the data used by researchers to arrive at their conclusions.Read moreRead less
Developing smart embedded host-based intrusion detection systems. Computer intrusion is a major concern in many places. It is estimated that cybercrime cost firms US$1 trillion globally in 2008. Many serious cyber attacks, including cyber espionage, do not generate significant network traffic and can easily penetrate network-based intrusion detection systems (NIDS). Such attacks often attempt to compromise individual hosts and hence they are best detected at the host level. We aim to design i ....Developing smart embedded host-based intrusion detection systems. Computer intrusion is a major concern in many places. It is estimated that cybercrime cost firms US$1 trillion globally in 2008. Many serious cyber attacks, including cyber espionage, do not generate significant network traffic and can easily penetrate network-based intrusion detection systems (NIDS). Such attacks often attempt to compromise individual hosts and hence they are best detected at the host level. We aim to design innovative host-based IDS, as a complement to the NIDS, to address this issue. The outcomes of this project will strengthen the national capability to resist attacks by criminals and terrorists on Australian networked critical infrastructures and also enhance the global competitiveness of Australia’s information technology industry.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH200100009
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Transforming Energy Infrastructure Through Digital Engineering. This Research Hub will harness the strengths of data-based and physics-based sciences to transform the operation of Australia’s offshore energy infrastructure. This essential research will create, use and embed observations of past and ongoing activity to engineer tools and approaches necessary to enhance our understanding of the offshore environment, optimise critical operations for existing facilities (includi ....ARC Research Hub for Transforming Energy Infrastructure Through Digital Engineering. This Research Hub will harness the strengths of data-based and physics-based sciences to transform the operation of Australia’s offshore energy infrastructure. This essential research will create, use and embed observations of past and ongoing activity to engineer tools and approaches necessary to enhance our understanding of the offshore environment, optimise critical operations for existing facilities (including installation and maintenance), and efficiently design future infrastructure. The integrated multidisciplinary approach will not only help Operators achieve high productivity through low downtime and optimised maintenance, but also demonstrate, in research and industry, the transformative potential of digital engineering.Read moreRead less
Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical ....Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical information, such as encryption keys, through timing channels. This should prevent sophisticated attacks on public clouds, mobile devices and military-grade cross-domain devices.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
Discovery Early Career Researcher Award - Grant ID: DE170101081
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis t ....Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis to efficiently and precisely analyse large-scale programs according to clients’ needs, thereby allowing compilers to generate safe, reliable and secure code. This project is expected to advance value-flow analysis for industrial-sized software, improve software reliability and security, and benefit Australian software systems and industries.Read moreRead less
Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with thei ....Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with their environment, and the simulation of spatiotemporal deformations in anatomical organs. Benefits include a better understanding of growth processes, predictive models of how degenerative diseases progress and a computational framework that will assist in designing proper mitigation and intervention strategies.Read moreRead less