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
Quantification of Multiphysics phenomena of Gas flow in organic rich shales. We address the scientific question of the nature of gas extraction from nominally impermeable rocks such as shales. Our main aim is to develop a fully coupled microstructurally enriched thermodynamic continuum model to predict the Multiphysics behaviour of shale reservoirs during gas production and verify the model with representative experiments conducted on formations from three Australian Basins including Cooper, Per ....Quantification of Multiphysics phenomena of Gas flow in organic rich shales. We address the scientific question of the nature of gas extraction from nominally impermeable rocks such as shales. Our main aim is to develop a fully coupled microstructurally enriched thermodynamic continuum model to predict the Multiphysics behaviour of shale reservoirs during gas production and verify the model with representative experiments conducted on formations from three Australian Basins including Cooper, Perth and Beetaloo, where the samples are available to the investigators. We approach this problem in a hybrid theoretical-numerical-experimental study. This is the first international attempt to develop such experimentally verified thermodynamic based model, particularly for Australian shales.Read moreRead less
Initiation of spontaneous fires. This project aims to determine the origin of the initiation reactions that set off the self-heating of wood chips, coal, milk powder and other economically-important materials, leading to spontaneous fires. This project will provide fundamental understanding of the reactions between electronically excited species of oxygen and carbonaceous fuels, with applications to improved safety in wood, mineral and food industries. The outcomes include identification of the ....Initiation of spontaneous fires. This project aims to determine the origin of the initiation reactions that set off the self-heating of wood chips, coal, milk powder and other economically-important materials, leading to spontaneous fires. This project will provide fundamental understanding of the reactions between electronically excited species of oxygen and carbonaceous fuels, with applications to improved safety in wood, mineral and food industries. The outcomes include identification of the initiation mechanisms and development of mechanistic models that include the initiation step of the self-heating process, and development of new technologies for mitigation of spontaneous fires, based on quenching of the initiation reactions.Read moreRead less
Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord ....Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.Read moreRead less
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
Predicting scour and scour-induced settlement of subsea infrastructure. This project aims to develop improved predictions and understanding of the potential and extent of scour and scour-induced settlement of subsea infrastructure on mobile seabeds. This is expected to enable scour and settlement to be accounted for directly in engineering stability and serviceability design, overturning current practice which ignores both effects on the basis of using scour protection and costly maintenance and ....Predicting scour and scour-induced settlement of subsea infrastructure. This project aims to develop improved predictions and understanding of the potential and extent of scour and scour-induced settlement of subsea infrastructure on mobile seabeds. This is expected to enable scour and settlement to be accounted for directly in engineering stability and serviceability design, overturning current practice which ignores both effects on the basis of using scour protection and costly maintenance and remediation. Development of accurate predictions is expected to be achieved through physical model testing, numerical modelling and analysis of field data. Predictions should improve subsea reliability and lead to omission of scour protection in some situations, increasing international competitiveness of our offshore oil and gas industry.Read moreRead less
Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less
Harnessing the power of oceans: anchors for floating energy devices. This project aims to establish a geotechnical design framework for shared anchoring systems subjected to multidirectional cyclic loading for large integrated arrays of floating wind turbines and floating wave energy converters. This is expected to facilitate new, economic foundation solutions, generating radical cost savings to help unlock Australia's renewable ocean energy resources. The project aims to utilise a blend of stat ....Harnessing the power of oceans: anchors for floating energy devices. This project aims to establish a geotechnical design framework for shared anchoring systems subjected to multidirectional cyclic loading for large integrated arrays of floating wind turbines and floating wave energy converters. This is expected to facilitate new, economic foundation solutions, generating radical cost savings to help unlock Australia's renewable ocean energy resources. The project aims to utilise a blend of state-of-the-art centrifuge modelling techniques and numerical modelling, incorporating an energy-based method and yield envelopes. This innovative methodology aims to establish a validated framework for understanding and predicting foundation performance under the complex load histories arising in renewable ocean energy applications.Read moreRead less
Developing innovative concrete composites by upscaling material properties. This project aims to develop an upscaling process to correlate micro-nano properties of engineering materials to their comprehensive physicochemical properties based on systematic mechanical and statistical analysis approaches and nanoindentation technology. The process will enable assessing material mechanical and viscoelastic properties at a microscale level thus will generate a new knowledge in structural engineering ....Developing innovative concrete composites by upscaling material properties. This project aims to develop an upscaling process to correlate micro-nano properties of engineering materials to their comprehensive physicochemical properties based on systematic mechanical and statistical analysis approaches and nanoindentation technology. The process will enable assessing material mechanical and viscoelastic properties at a microscale level thus will generate a new knowledge in structural engineering discipline including health monitoring, assessment of existing structures, historical buildings, and strengthening and repairing materials in structures. The outcomes are a multiscale link model for upscaling material properties and a development of innovative reinforced concrete composites which are cost-effective and efficient.Read moreRead less
Geopolymer concrete for thin-walled structures in marine environment. This project aims to develop ultra-high performance geopolymer concrete thin-walled structures for the critical infrastructure in the marine environment. It is expected that this project will develop novel design rules for ultra-high performance geopolymer concrete thin-walled structures based on experimental testing, numerical modelling, validation, and simulation. This project is expected to increase the durability of coasta ....Geopolymer concrete for thin-walled structures in marine environment. This project aims to develop ultra-high performance geopolymer concrete thin-walled structures for the critical infrastructure in the marine environment. It is expected that this project will develop novel design rules for ultra-high performance geopolymer concrete thin-walled structures based on experimental testing, numerical modelling, validation, and simulation. This project is expected to increase the durability of coastal infrastructures and significantly reduce the loss of their capacities due to corrosion-induced damage. The development of ultra-high performance geopolymer concrete thin-walled structures is a significant engineering discovery, which is in line with the Australian government 2030 vision for sustainable development.Read moreRead less