Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the effici ....Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the efficiency and accuracy of product tracking in distribution networks. This project will place Australia at the forefront of RFID research. It will also be an excellent vehicle for educating young researchers and engineers in Australia.Read moreRead less
Towards Scalable, Internet-Based RFID Traceability Networks. Food and drug safety is a major public health issue in Australia. Recent events involving poisoning of chocolate bars and paracetamol tablets in Australia have demonstrated the urgent need for improved ways of locating and recalling commercial products that have been released into the community. This project will develop novel techniques for locating items in large-scale distribution networks driven by RFID (Radio Frequency Identificat ....Towards Scalable, Internet-Based RFID Traceability Networks. Food and drug safety is a major public health issue in Australia. Recent events involving poisoning of chocolate bars and paracetamol tablets in Australia have demonstrated the urgent need for improved ways of locating and recalling commercial products that have been released into the community. This project will develop novel techniques for locating items in large-scale distribution networks driven by RFID (Radio Frequency Identification) technology. The outcomes of the project will make it easier to rapidly and accurately pinpoint product locations in the event of problems such as an illness outbreak due to contaminated food or counterfeited drugs. Read moreRead less
Normalizing XML Documents. Our work will be of great benefit, both to the research community and to the ICT industry. The project addresses one of the most important problems in XML usage and we expect our results to be published in important international forums, as has our preliminary research on the topic. This will significantly improve Australia's reputation in research in the ICT area. In the longer term, we intend to build commercial software tools based on the results of our research ....Normalizing XML Documents. Our work will be of great benefit, both to the research community and to the ICT industry. The project addresses one of the most important problems in XML usage and we expect our results to be published in important international forums, as has our preliminary research on the topic. This will significantly improve Australia's reputation in research in the ICT area. In the longer term, we intend to build commercial software tools based on the results of our research and this will be of direct benefit to the Australian economy and the Australian ICT industry.Read moreRead less
Privacy-Preserving Classification for Big-Data Driven Network Traffic. Protecting sensitive information in large network traffic flows while ensuring data usability for classification emerges as a critical problem of increasing significance. Existing techniques do not work on highly heterogeneous traffic from big-data applications for both privacy protection and classification (such as port-based and load- based methods). This project investigates new theories, methods and techniques for solving ....Privacy-Preserving Classification for Big-Data Driven Network Traffic. Protecting sensitive information in large network traffic flows while ensuring data usability for classification emerges as a critical problem of increasing significance. Existing techniques do not work on highly heterogeneous traffic from big-data applications for both privacy protection and classification (such as port-based and load- based methods). This project investigates new theories, methods and techniques for solving this problem. It proposes to develop a set of effective methods for privacy-preserving data publication through combining randomisation with anonymisation, and for classifying the published data through uncertainty leveraging by probabilistic reasoning and accuracy lifting by inter-flow correlation analysis and active learning.Read moreRead less