Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less
Analysis and classification of malicious code. Malicious software such as viruses and worms directly attacks the security, privacy and integrity of Australian e-commerce, large databases and communication channels. The recent uptake of malicious software by organised crime has made finding effective countermeasures more urgent. Around 80% of the malicious code in circulation is disguised in some way. This significantly increases the difficulty of automated detection and delays analysis. Automate ....Analysis and classification of malicious code. Malicious software such as viruses and worms directly attacks the security, privacy and integrity of Australian e-commerce, large databases and communication channels. The recent uptake of malicious software by organised crime has made finding effective countermeasures more urgent. Around 80% of the malicious code in circulation is disguised in some way. This significantly increases the difficulty of automated detection and delays analysis. Automated classification and de-obfuscation technologies are a precondition to applying more sophisticated detection heuristics. The project will be instrumental in safeguarding Australia by protecting critical infrastructure and defending us from online organised crime and information warfare.Read moreRead less
Practical unified framework for secure e-consent mechanism for health records. This project is driven by modern applications of cryptography and network security and their applications in securing e-health by enabling secure Personal Health Records (PHRs), which will play an important role in the future healthcare industry.
A new spectrum access technology for future wireless terminals. This project will develop a new frequency flexible wireless transceiver structure for the next generation of smartphones and wireless devices. The project will improve the roaming experience of travellers and reduce the cost of wireless connectivity, enabling new applications such as machine-to-machine communications and the internet-of-things.
Tools and models for measuring and predicting growth in internet addressing and routing complexity. We analyse patterns in the allocation and actual use of Internet Protocol version 4 (IPv4) addresses to predict the technical and market pressures for deployment of IPv6. The utilisation models will help evaluate the potential for emerging markets in scarce IPv4 address prefixes to increase costs to the end-users of Australia's future national broadband network.
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
Intruder alert! detecting and classifying events in noisy time series. This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enabl ....Intruder alert! detecting and classifying events in noisy time series. This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enable improved event detection and classification in noisy time series to the benefit of many critical application areas beyond national security.Read moreRead less
Personalised topic modelling and sentiment analysis for enhanced information discovery over document streams. This project will develop personalised information discovery, navigation and management systems of online content for the creative industries, e.g. to help advertising agencies understand market trends, and enable designers to discover and analyse information relating to new product concepts.
The evolution of Australian enterprises, 1990 to 2007 : An empirical analysis of the relationship between turbulence among firms, productivity, growth and exports. This project will examine determinants and effects of enterprise entry and exit on growth, export and productivity in Australian industry using innovative panel enterprise data sets which have been collated and linked from existing ABS surveys, administrative data and accounting data. Currently, there is only one short longitudinal en ....The evolution of Australian enterprises, 1990 to 2007 : An empirical analysis of the relationship between turbulence among firms, productivity, growth and exports. This project will examine determinants and effects of enterprise entry and exit on growth, export and productivity in Australian industry using innovative panel enterprise data sets which have been collated and linked from existing ABS surveys, administrative data and accounting data. Currently, there is only one short longitudinal enterprise data set in Australia. Further data sets are required if policy makers are to understand patterns and causes of growth and business survival in Australia. Understanding provided from these studies should significantly improve our undertanding of how businesses perform.Read moreRead less
Robust and scalable change detection in geo-spatial data. A flood of data in the form of text, images and video emanate from a proliferation of sensors. These data are collected but rarely analysed, rendering it meaningless. This project aims to develop new software and techniques to detect changes over time in large scale geographically referenced data (for example photomaps) for use across numerous domains.