Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a n ....Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a new data management and processing foundation for big video data analytics.Read moreRead less
Contextual Behabiour Predictions in Dynamic Mobile E-commerce. The project aims to address behaviour prediction and develop novel techniques and tools for modelling, predicting human behaviours and making effective recommendations based on ubiquitous user behaviour data in mobile e-commerce. The techniques enable multi-source data fusion, context learning and model adaptation, and dynamic recommendation with interpretability ability. Expected outcomes include advances in data analytics theory an ....Contextual Behabiour Predictions in Dynamic Mobile E-commerce. The project aims to address behaviour prediction and develop novel techniques and tools for modelling, predicting human behaviours and making effective recommendations based on ubiquitous user behaviour data in mobile e-commerce. The techniques enable multi-source data fusion, context learning and model adaptation, and dynamic recommendation with interpretability ability. Expected outcomes include advances in data analytics theory and informed decision-making. This provides significant benefits of not only placing Australia in the forefront of exploiting multimodal user behaviour big data in dynamic e-commerce but also transforming Australian government and businesses to intelligent and contextual services adaptive to complex situations.Read moreRead less
Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop ne ....Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop new privacy-preserving algorithms on EHD database federations, which can provide efficient data access yet block inside attacks. It will significantly improve the data available for medical research, while reducing the cost of EHD system management and providing visualised decision supports to medical staff and the government health resource planners.Read moreRead less
Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage ....Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage capabilities, including graphics processor and flash-based memory. This project will devise an adaptive key-value store framework for heterogeneous systems. Our new framework will adaptively harvest the performance potential of future hardware such that applications can cope with fast-growing data sets.Read moreRead less
What Can You Trust in the Large and Noisy Web? This project will develop innovative techniques to efficiently and effectively distill truthful information from the inherently unreliable and large-scale Web environment, where misinformation has been widely regarded as a grand challenge for the next decade. The results of this project will not only maintain Australia’s leadership in this frontier research area, but also support many important applications that safeguard Australian people and econo ....What Can You Trust in the Large and Noisy Web? This project will develop innovative techniques to efficiently and effectively distill truthful information from the inherently unreliable and large-scale Web environment, where misinformation has been widely regarded as a grand challenge for the next decade. The results of this project will not only maintain Australia’s leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as emergency and disaster management and online healthcare. This project also serves as an excellent vehicle for the education and training of Australia’s next generation of scholars and engineers.Read moreRead less
Classifying Internet traffic for security applications. As the internet traffic data exponentially increases every year, traffic classification has become a fundamental approach to the security of the Internet. This project aims to develop a set of novel techniques for internet traffic classification, which is fundamentally important to defend against the serious cyber-attacks and effectively minimise the damages. This project is significant as it can help to improve cyber security, which is ess ....Classifying Internet traffic for security applications. As the internet traffic data exponentially increases every year, traffic classification has become a fundamental approach to the security of the Internet. This project aims to develop a set of novel techniques for internet traffic classification, which is fundamentally important to defend against the serious cyber-attacks and effectively minimise the damages. This project is significant as it can help to improve cyber security, which is essential for the work and daily lives of the Australian people. Furthermore, the proposed models and techniques will be important for enhancing the protection of Australian critical infrastructures against malicious cyber-attacks.Read moreRead less
Improving provision of a document store as a service in a public cloud. Improving provision of a document store as a service in a public cloud. This project aims to develop a model of document-oriented database correctness and performance that can be applied to cloud-hosted clusters. Many modern web applications rely on document-oriented databases hosted on clusters of virtualised servers from commercial cloud providers. Developers make difficult deployment decisions, such as how to combine data ....Improving provision of a document store as a service in a public cloud. Improving provision of a document store as a service in a public cloud. This project aims to develop a model of document-oriented database correctness and performance that can be applied to cloud-hosted clusters. Many modern web applications rely on document-oriented databases hosted on clusters of virtualised servers from commercial cloud providers. Developers make difficult deployment decisions, such as how to combine data sharding and replication to meet service requirements without any guidance on the degree of precision. This research will allow developers and database administrators to predict how systems will behave in conditions difficult to simulate directly. Ultimately, this is expected to improve the quality and efficiency of services built using document databases.Read moreRead less
A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword ....A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword search, subgraph isomorphism and substructure query techniques. This project is expected to significantly accelerate the application of new technologies, for example, big data analytics and Internet of Things, in many of Australia's critical domains such as e-Health, smart cities, and cybersecurity.Read moreRead less
Integrating Quality Control into Crowd-sourcing Services. This project aims to contribute to the scientific foundations of quality control in crowd-sourcing services. Crowd-sourcing services harness the wisdom of large communities to solve problems. Open projects (eg Linux, Wikipedia) have successfully used crowd sourcing. Increasingly, organisations and governments are using crowd-sourcing to improve products and services. However, there are significant risks due to lack of robust quality contr ....Integrating Quality Control into Crowd-sourcing Services. This project aims to contribute to the scientific foundations of quality control in crowd-sourcing services. Crowd-sourcing services harness the wisdom of large communities to solve problems. Open projects (eg Linux, Wikipedia) have successfully used crowd sourcing. Increasingly, organisations and governments are using crowd-sourcing to improve products and services. However, there are significant risks due to lack of robust quality control methods. The project aims to contribute to the first methodology and techniques for systematic provisioning of robust crowd-sourcing quality control mechanisms. It is expected that project outcomes would contribute to lifting productivity and economic growth through quality-aware crowd sourcing service technologies.Read moreRead less
Decentralised Collaborative Predictive Analytics on Personal Smart Devices. This project tackles the challenging problem of personalised predictive analytics with resource-constrained personal devices and massive-scale data. The knowledge to be generated concerns privacy, fairness, and resource efficiency in the era of Internet of Things. The expected outcomes include a collaborative learning paradigm for building personalised models on personal smart devices in open and fully decentralised sett ....Decentralised Collaborative Predictive Analytics on Personal Smart Devices. This project tackles the challenging problem of personalised predictive analytics with resource-constrained personal devices and massive-scale data. The knowledge to be generated concerns privacy, fairness, and resource efficiency in the era of Internet of Things. The expected outcomes include a collaborative learning paradigm for building personalised models on personal smart devices in open and fully decentralised settings. Privacy and model fairness are core tenets of the paradigm. Personalised predictive analytics is frontier research that will position Australia at the forefront of AI and give business the tools needed to deploy innovative business systems for market exploitation with a secure, equitable and competitive advantage.Read moreRead less