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
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
Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical b ....Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical books. Libraries and legal, social and data science researchers will investigate eBook lending practices and understand their social impacts. The project will identify ways of reforming policy, law, and practice to help libraries fulfil their public interest missions. This project is expected to enable libraries to extract more value from existing public investments.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
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100156
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Computational infrastructure for machine learning in computer vision. The many trillions of images stored on computers around the world, including more than 100 billion on Facebook alone, represent exactly the information needed to develop artificial vision. All we need do is extract it. This project will develop the computational infrastructure required to allow Australian researchers to achieve this goal.
Signal Processing for Reconfigurable Antennas – a Multidisciplinary Approach for Next Generation Wireless Communications. To satisfy the enormous demand for wireless applications with scarce radio spectrum, new technologies must be researched, developed, and then employed. Reconfigurable antennas, through morphing their physical structures with various switches, can adapt to the radio propagation environment, thereby increasing spectrum efficiency and power efficiency of wireless communications. ....Signal Processing for Reconfigurable Antennas – a Multidisciplinary Approach for Next Generation Wireless Communications. To satisfy the enormous demand for wireless applications with scarce radio spectrum, new technologies must be researched, developed, and then employed. Reconfigurable antennas, through morphing their physical structures with various switches, can adapt to the radio propagation environment, thereby increasing spectrum efficiency and power efficiency of wireless communications. This project aims to design signal processing algorithms for achieving all the benefits that reconfigurable antennas can provide for wireless communications. An important outcome of this research is sound channel models validated by extensive field measurement data.Read moreRead less
Special Research Initiatives - Grant ID: SR0354729
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
Smart Use of Information Technologies (SUITs). The SUITs network will develop critical mass in world-class, leading-edge research into the smart use of information and communication technology (ICT) through integration of research within the dispersed Australian ICT research community and through facilitating international linkages. The network will undertake research applicable in key sectors including the health, education, service, knowledge and media industries. The aim is to establish a h ....Smart Use of Information Technologies (SUITs). The SUITs network will develop critical mass in world-class, leading-edge research into the smart use of information and communication technology (ICT) through integration of research within the dispersed Australian ICT research community and through facilitating international linkages. The network will undertake research applicable in key sectors including the health, education, service, knowledge and media industries. The aim is to establish a higher order of coordination and collaboration in research into ICT applications.
The feasibility study proposed will engage key stakeholders, refine research goals and investigate linkage mechanisms to improve Australia's ICT research and its contribution to economic and social well-being.
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Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa ....Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.Read moreRead less
Economically efficient green logistics through cyber physical systems. Economically efficient green logistics through cyber physical systems. This project aims to realize green logistics by researching how to run diesel-powered heavy-duty milk trucks economically and efficiently on liquefied natural gas (LNG) and demonstrating to logistics companies that LNG conversion will reduce operating costs and emissions. Transportation systems account for 18% of Australia's carbon emissions, and diesel-po ....Economically efficient green logistics through cyber physical systems. Economically efficient green logistics through cyber physical systems. This project aims to realize green logistics by researching how to run diesel-powered heavy-duty milk trucks economically and efficiently on liquefied natural gas (LNG) and demonstrating to logistics companies that LNG conversion will reduce operating costs and emissions. Transportation systems account for 18% of Australia's carbon emissions, and diesel-powered logistics vehicles are a major contributor. However, converting these trucks to LNG requires strong evidence to convince logistics companies of the benefits of shifting to green logistics. An increase in logistics productivity is expected to increase Australia’s gross domestic product by $2 billion, while this research should also provide vital data on sustainability issues and LNG conversions.Read moreRead less