A novel quantitative risk assessment framework for fractured rock slopes. Rock slope instabilities present grave risks to life and to the serviceability of major Australian infrastructure such as mines, roads and railways, and to coastal recreation areas. This project aims at developing tools for the quantitative risk assessment of fractured rock slopes based on rigorous rock mechanics, numerical methods and probabilistic methods.
The research outcomes will improve our understanding of natural ....A novel quantitative risk assessment framework for fractured rock slopes. Rock slope instabilities present grave risks to life and to the serviceability of major Australian infrastructure such as mines, roads and railways, and to coastal recreation areas. This project aims at developing tools for the quantitative risk assessment of fractured rock slopes based on rigorous rock mechanics, numerical methods and probabilistic methods.
The research outcomes will improve our understanding of natural and engineering rock slopes, reduce the uncertainties in the prediction of the safety of infrastructures, and thus minimize the loss and damage. The research outcomes can also be used to maintain workplace safety in mining environments and avoid disruptions to production.
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Unravelling soil carbon response to warming in fire-affected ecosystems. This project aims to reveal the continental pattern of soil carbon (C) response to warming in fire-affected ecosystems across Australia and to unravel the biogeochemical mechanisms underlying fire’s role in shaping the temperature sensitivity of soil respiration. Fire has modified over 40% of the Earth’s land surface and wildfire frequency is predicted to increase under global warming. This project expects to generate new k ....Unravelling soil carbon response to warming in fire-affected ecosystems. This project aims to reveal the continental pattern of soil carbon (C) response to warming in fire-affected ecosystems across Australia and to unravel the biogeochemical mechanisms underlying fire’s role in shaping the temperature sensitivity of soil respiration. Fire has modified over 40% of the Earth’s land surface and wildfire frequency is predicted to increase under global warming. This project expects to generate new knowledge on how fire influences soil-to-atmosphere C fluxes in a warmer climate using a multi-disciplinary approach. Expected outcomes include an enhanced capacity to predict the terrestrial ecosystem-to-atmosphere C fluxes and their feedbacks to climate under increasing frequency of fire using Earth-system models. 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
Formation and stabilisation of coastal blue carbon. Blue carbon is organic carbon stored within coastal vegetated ecosystems. This project will examine the composition, formation and dynamics of blue carbon in a range of coastal ecosystems. Combining advanced analytical chemistry with environmental microbiology, we will discover how blue carbon is stabilised and destabilised, a critical factor in nature-based climate change mitigation strategies. Further, we will gain a quantitative understandin ....Formation and stabilisation of coastal blue carbon. Blue carbon is organic carbon stored within coastal vegetated ecosystems. This project will examine the composition, formation and dynamics of blue carbon in a range of coastal ecosystems. Combining advanced analytical chemistry with environmental microbiology, we will discover how blue carbon is stabilised and destabilised, a critical factor in nature-based climate change mitigation strategies. Further, we will gain a quantitative understanding of blue carbon contributions to carbon cycling, providing enhanced modeling and prediction of climate-cycle feedbacks in response to biotic and environmental change. This research will significantly benefit Australia’s effective management of coastal vegetated ecosystems for maximum carbon offsets.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less
Building insights of our largest terrestrial carbon sink: rangelands soils. Rangelands soils represent Australia’s largest carbon sink. Yet, little is known about their potential for carbon sequestration or their vulnerability to climate and environmental change. This project leverages investments in national terrestrial observation platforms and integrates previous research outputs to develop new methods to measure and build understanding of soil carbon composition and dynamics in rangeland eco ....Building insights of our largest terrestrial carbon sink: rangelands soils. Rangelands soils represent Australia’s largest carbon sink. Yet, little is known about their potential for carbon sequestration or their vulnerability to climate and environmental change. This project leverages investments in national terrestrial observation platforms and integrates previous research outputs to develop new methods to measure and build understanding of soil carbon composition and dynamics in rangeland ecosystems. Under a framework that connects detailed measurements and small-scale processes, with machine-learning, data-model assimilation and large-scale next-generation biogeochemical modelling, it’ll allow more accurate predictions of soil carbon change and better decision-making to guide sustainable rangelands management.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
The growth of giant black holes in the early universe. This project aims to discover the largest black holes in the early universe and their origin, and weigh them using infrared spectroscopy. Giant black holes at the centres of galaxies reach masses over ten billion times that of our Sun. Astronomy has revealed the origin of black holes with masses similar to that of the Sun, but remains puzzled by the existence of those with masses many million times larger. This project will reveal pathways o ....The growth of giant black holes in the early universe. This project aims to discover the largest black holes in the early universe and their origin, and weigh them using infrared spectroscopy. Giant black holes at the centres of galaxies reach masses over ten billion times that of our Sun. Astronomy has revealed the origin of black holes with masses similar to that of the Sun, but remains puzzled by the existence of those with masses many million times larger. This project will reveal pathways of black-hole growth early after the Big Bang. The project will shed light on the evolution of galaxies in the early universe and prepare the ground for new work by other scientists, for example on the origin of the elements.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
Improving the specificity of affective computing via multimodal analysis. This project aims to develop multimodal affective sensing techniques that can sense very subtle expressions in human moods and emotions. Much research in affective computing has investigated ways to improve the sensitivity of affect sensing approaches, resulting in more accurate estimates of affective states such as emotions or mood. What remains unsolved so far is the issue of specificity. This project will address this i ....Improving the specificity of affective computing via multimodal analysis. This project aims to develop multimodal affective sensing techniques that can sense very subtle expressions in human moods and emotions. Much research in affective computing has investigated ways to improve the sensitivity of affect sensing approaches, resulting in more accurate estimates of affective states such as emotions or mood. What remains unsolved so far is the issue of specificity. This project will address this issue through novel analyses of very subtle cues in facial and vocal expressions of affect embedded in a multimodal deep learning framework. Current approaches can successfully assist in binary classification tasks. This project will tackle the much more difficult problem of developing advanced affective sensing technology to simultaneously handle homogeneous and heterogeneous affect classes as well as continuous range estimates of affect intensity.Read moreRead less