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
Novel audio watermarking techniques for tracing multimedia piracy. This project aims to develop inaudible, high-capacity audio watermarking techniques to trace the illegal copying and distribution of multimedia data containing a sound component, such as audios and sound videos. With the rapid growth of communication networks and the use of advanced multimedia technology, digital multimedia data can be easily copied, manipulated and distributed. This has led to strong demand for new techniques to ....Novel audio watermarking techniques for tracing multimedia piracy. This project aims to develop inaudible, high-capacity audio watermarking techniques to trace the illegal copying and distribution of multimedia data containing a sound component, such as audios and sound videos. With the rapid growth of communication networks and the use of advanced multimedia technology, digital multimedia data can be easily copied, manipulated and distributed. This has led to strong demand for new techniques to prevent illegal use of copyrighted data. The project is expected to advance the theory of audio watermarking and enhance Australia's international competitiveness in this field.
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A provable privacy-preserving data sharing system for the cloud environment. This project aims to develop an innovative data sharing system, with a mathematically provable privacy guarantee, in a cloud environment. This will be adopted by Australian Education Management Group’s (AEMG) cloud campus to exchange data in a restricted privacy manner between partner institutions. It will be commercialised as a middleware that can be plugged into existing cloud environments to maintain required privacy ....A provable privacy-preserving data sharing system for the cloud environment. This project aims to develop an innovative data sharing system, with a mathematically provable privacy guarantee, in a cloud environment. This will be adopted by Australian Education Management Group’s (AEMG) cloud campus to exchange data in a restricted privacy manner between partner institutions. It will be commercialised as a middleware that can be plugged into existing cloud environments to maintain required privacy even when the cloud crosses various jurisdictions with different privacy policies. The outcomes will benefit educational organisations, and lay the foundations for data sharing in other communities such as the government, banks, and other industries in Australia.Read moreRead less