Post-Quantum Functional Encryption : Principles, Protocols and Practice. Modern cryptography has the power to revolutionise virtually every aspect of our online lives. Large-scale secure data sharing could become a breeze, with tools such as functional encryption (FE) to give us fine control over access rights by means of expressive languages, and there will be no more juggling of crypto keys. Finally, the known foundations of FE will crumble when even small-sized quantum computers become realit ....Post-Quantum Functional Encryption : Principles, Protocols and Practice. Modern cryptography has the power to revolutionise virtually every aspect of our online lives. Large-scale secure data sharing could become a breeze, with tools such as functional encryption (FE) to give us fine control over access rights by means of expressive languages, and there will be no more juggling of crypto keys. Finally, the known foundations of FE will crumble when even small-sized quantum computers become reality, perhaps next decade. This project aims to recreate and expand the power of FE from post-quantum (PQ) mathematical principles, immune to quantum attacks, building on recent discoveries of limited forms of PQ-FE from rock-solid crypto principles. It begs exploring, for the truly spectacular outcomes likely to ensue.Read moreRead less
Real-time Event Detection, Prediction, and Visualization for Emergency Response. This project proposes novel end-to-end methods for real-time recognition and prediction of real-world events, leading to timely response to emergencies such as disease outbreaks and natural disasters, as well as prevention of crime, security breaches and the like. It will develop new techniques to quickly detect and predict events by incorporating adaptive learning and probabilistic models, and address fusion and sc ....Real-time Event Detection, Prediction, and Visualization for Emergency Response. This project proposes novel end-to-end methods for real-time recognition and prediction of real-world events, leading to timely response to emergencies such as disease outbreaks and natural disasters, as well as prevention of crime, security breaches and the like. It will develop new techniques to quickly detect and predict events by incorporating adaptive learning and probabilistic models, and address fusion and scalability factors to handle vast collections of heterogeneous data. An event surveillance system prototype will be developed to incorporate the findings of the research with tools to visualise and describe events.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100308
Funder
Australian Research Council
Funding Amount
$300,000.00
Summary
Mobile User Modeling for Intelligent Recommendation. This project aims to develop effective and efficient techniques to enable individuals, business and government to better understand and exploit knowledge in human daily activity data and to provide higher quality mobile recommendation services such as personalised trip planning and tourist services. The project intends to develop a mobile user modelling framework which accurately infers mobile users' location-time-dependent interests and spa ....Mobile User Modeling for Intelligent Recommendation. This project aims to develop effective and efficient techniques to enable individuals, business and government to better understand and exploit knowledge in human daily activity data and to provide higher quality mobile recommendation services such as personalised trip planning and tourist services. The project intends to develop a mobile user modelling framework which accurately infers mobile users' location-time-dependent interests and spatial mobility patterns from their daily activity records and social ties in geo-social networks. It then intends to combine this knowledge to build an intelligent recommender system. The project outcomes and techniques could be applied in various location-based services, mobile advertising and marketing.Read moreRead less
Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this projec ....Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this project will be suitable for more than medical surveillance data; it will also improve the processing of other kinds of massive stream data (for example data from remote sensors, communication networks and other dynamic environments). The project involves a scientifically rich collaboration that will enhance the skills of PhD students and staff and drive the field forward.Read moreRead less
Special Research Initiatives - Grant ID: SR0354476
Funder
Australian Research Council
Funding Amount
$20,000.00
Summary
Intelligent Applications Through The Semantic Web. The primary aim of the proposed bid is to build a network of Australian researchers and their international peers for condresearch into the fundamental as well as applied aspects of the Semantic Web. By incorporating meaning of web-content in a form that can be accessed and processed by intelligent software agents, the Semantic Web will allow computers and humans to work in cooperation. This research will address the needs of both the Australian ....Intelligent Applications Through The Semantic Web. The primary aim of the proposed bid is to build a network of Australian researchers and their international peers for condresearch into the fundamental as well as applied aspects of the Semantic Web. By incorporating meaning of web-content in a form that can be accessed and processed by intelligent software agents, the Semantic Web will allow computers and humans to work in cooperation. This research will address the needs of both the Australian government and industry that provide and make smart use of information available on the Web. It will ensure Australian preparedness for the next-generation web technology.Read moreRead less
Detection of location significance from quality enhanced trajectory data. This project aims to develop effective and efficient methods to utilise large scale Global Positioning System, route and location data to provide individuals, business, government and social groups, the ability to assess the relative significance of locations and associated services, for use in applications such as transportation, logistics, public safety, tourism and utilities.
In-memory moving objects analytics for real-time business applications. This project aims to develop a novel computing foundation based on in-memory technologies to address significant challenges of big data and location-based business intelligence, building upon the well-recognised research excellence in spatiotemporal data management at the University of Queensland, and HANA, SAP's (Systems, Applications, Products in data processing) new in-memory analytics platform.
Declaration, Exploration, Enhancement and Provenance: The DEEP Approach to Data Quality Management Systems. The project proposes the Declaration, Exploration, Enhancement, Provenance (DEEP) approach to data quality management. The approach adopts a whole-of-data-cycle view towards addressing complex and emerging problems in data quality management and aims to develop novel and comprehensive mechanisms to improve data quality measurement, enforcement and monitoring. Due to the application-centric ....Declaration, Exploration, Enhancement and Provenance: The DEEP Approach to Data Quality Management Systems. The project proposes the Declaration, Exploration, Enhancement, Provenance (DEEP) approach to data quality management. The approach adopts a whole-of-data-cycle view towards addressing complex and emerging problems in data quality management and aims to develop novel and comprehensive mechanisms to improve data quality measurement, enforcement and monitoring. Due to the application-centric nature of DEEP, the outcomes from the project are expected to increase user understanding of data characteristics, improve interpretability of information derived from large, multi-source data sets and contribute to enhancement of data literacy levels in involved user communities. Read moreRead less
QualA-D: a quality aware query engine for next generation data integration systems. This project will address the growing diversity of the web/user community by developing new approaches for data integration that incorporate data quality requirements such as data currency, completeness and coverage. First-of-breed quality aware query system is expected to be developed that will assist in improving user experience and satisfaction.
Discovery Early Career Researcher Award - Grant ID: DE140100215
Funder
Australian Research Council
Funding Amount
$394,752.00
Summary
Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genui ....Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genuine preferences from travel histories, due to lack of consideration for activity information as well as the associated semantics and context. This project aims to address these issues and provide effective recommendations by considering both users’ intention and collective behavioural knowledge inferred from activity trajectories.Read moreRead less