BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation fra ....BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation framework with associated algorithms and its prototype, which cloud systems can deploy for big data applications.Read moreRead less
Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over ti ....Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over time and captured by different sensors and identify correlations between historic security incidents and current data attacks. This project will significantly help to secure data on cloud for organisations in Australia and benefit fast-growing security sensitive data hosting and applications on cloud.Read moreRead less
Data Exchange and Service Integration with Applications in Health Information Systems. This project will research and develop an innovative new approach to facilitate real data exchange and service integration across different medical organisations. This approach will significantly improve the quality of health care by providing a solid foundation for integrated medical services, offering on demand and effective access to fragmentally stored patients medical information and minimise the number o ....Data Exchange and Service Integration with Applications in Health Information Systems. This project will research and develop an innovative new approach to facilitate real data exchange and service integration across different medical organisations. This approach will significantly improve the quality of health care by providing a solid foundation for integrated medical services, offering on demand and effective access to fragmentally stored patients medical information and minimise the number of data entry errors injected into the medical information systems. The novel integration model will also enable a new autonomous approach for demographic data collection which is essential for evidenced resource allocation, policy making and disease prevention.Read moreRead less
Continuous and summarised search over evolving heterogeneous data. The project aims to design a search engine that monitors and retrieves over multiple social media and micro-blogging platforms. The engine presents search results in a personalised continuously updated summary. An inverted index structure systematically captures and provides easy access to all monitored content, including text, linked and relational data. The structure enables a continuous search paradigm that tracks updates on b ....Continuous and summarised search over evolving heterogeneous data. The project aims to design a search engine that monitors and retrieves over multiple social media and micro-blogging platforms. The engine presents search results in a personalised continuously updated summary. An inverted index structure systematically captures and provides easy access to all monitored content, including text, linked and relational data. The structure enables a continuous search paradigm that tracks updates on both the content and popularity of search results. This is expected to help organisations and governments track, understand and exploit social media.Read moreRead less
Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling rese ....Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling research and practical solutions for this important cloud and big data research area; benefiting key big data application areas on the cloud, such as hospitals, insurance companies and government information services; and helping to maintain Australia at the forefront of cloud and big data research with innovative industry applications.Read moreRead less
Managing private location data in a mobile and networked world: getting the balance right. Location based data are transforming the mobile service industry and this project will develop novel approaches to safeguard the location privacy of mobile individuals. This will facilitate the development of privacy-aware services which can be used for real time traffic monitoring, care for the elderly and smartphone enabled location services.
Mobile Query Processing: An Integrated Approach. Mobile communication is a frontier technology, and providing efficient mobile query services to the general public is critical in placing Australia as a leading country in mobile information services. The benefit to Australia nationally is beyond the telecommunication industry. The project will transform other Australian industries which rely on mobile information services, including emergency response services (eg. ambulance, police), mobile work ....Mobile Query Processing: An Integrated Approach. Mobile communication is a frontier technology, and providing efficient mobile query services to the general public is critical in placing Australia as a leading country in mobile information services. The benefit to Australia nationally is beyond the telecommunication industry. The project will transform other Australian industries which rely on mobile information services, including emergency response services (eg. ambulance, police), mobile workforce and mobile commerce, transportation/traffic controller, bureau of meteorology, defence/army forces, financial market, as well as tourism and news. With the enormous growing of investment in these industries, this project will become a major contribution to national productivity and growth.Read moreRead less
Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and ....Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and efficient algorithms for searching and monitoring cohesive subgraphs in big and dynamic attributed graphs from both structure and attribute perspectives. The methods, techniques, and prototype systems developed in this project can be deployed to facilitate the smart use of big graph data across the nation. Read moreRead less
Effective and efficient keyword search for relevant entities over Extensible Markup Language (XML) data. This project aims to greatly improve the relevancy of returned XML entities by keyword queries as well as the efficiency of searching. Effective approaches and efficient algorithms for finding relevant entities from large number of XML data sources will be delivered.
Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for differen ....Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for different applications and devise efficient algorithms for searching and monitoring those cohesive groups based on different models. The methods, techniques, and evaluation systems developed in this project can be deployed to facilitate the smart use of heterogeneous information networks across the nation.Read moreRead less