Privacy preservation for personalised smart devices. The goal of this project is to build a privacy preservation framework for personalised smart devices with both immediate and long-term applications in a range of industries. The novel theoretical contributions include a privacy-preservation mechanism that guards against attacks by intelligent tools, a model and metrics that distinguish between object detection and object recognition, and allowing users to specify their desired level of privacy ....Privacy preservation for personalised smart devices. The goal of this project is to build a privacy preservation framework for personalised smart devices with both immediate and long-term applications in a range of industries. The novel theoretical contributions include a privacy-preservation mechanism that guards against attacks by intelligent tools, a model and metrics that distinguish between object detection and object recognition, and allowing users to specify their desired level of privacy guarantee. Practically, these solutions have clear economic and public-safety benefits. The solutions will accelerate AI device development, advance smart technologies based on individual behaviours, and guarantee personal data privacy against both human attackers and adversarial algorithms. Read moreRead less
Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges ....Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges and expects to establish innovative research and solutions for enabling full lifecycle privacy protection on cloud. The project outcomes will help to safeguard Australian community in fast-growing online cyber world, and benefit to fast-growing privacy sensitive data hosting and applications on cloud.Read moreRead less
Visual Analytics for Next Generation Sequencing. Next-generation sequencing technologies have brought a revolution in biology and healthcare, while taxing the ability of scientists and clinicians to identify and process relevant data, to make sense of it all and communicate it to others in a concise and meaningful way. This project aims to tackle this problem through fundamentally new approaches to data selection and visualisation at very large scale, actively encoding for insight into underlyin ....Visual Analytics for Next Generation Sequencing. Next-generation sequencing technologies have brought a revolution in biology and healthcare, while taxing the ability of scientists and clinicians to identify and process relevant data, to make sense of it all and communicate it to others in a concise and meaningful way. This project aims to tackle this problem through fundamentally new approaches to data selection and visualisation at very large scale, actively encoding for insight into underlying biological and biomedical processes, bringing sustainable discovery of new relationships and variations within the data. The project aims to support new approaches to medical diagnosis and treatment, and offer crucial lessons to address the broader challenge of understanding large, complex data sets.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
Virtual Environments for Improved Enterprise Software Deployment. This project aims to improve quality assurance for enterprise IT. Enterprise IT systems are highly interconnected and interdependent — a failure in one system can cause a cascade of failures across multiple systems, bringing business to a standstill. The project aims to create new technologies to automate the provisioning of virtual deployment environments to test the enterprise systems. In particular, it aims to develop new metho ....Virtual Environments for Improved Enterprise Software Deployment. This project aims to improve quality assurance for enterprise IT. Enterprise IT systems are highly interconnected and interdependent — a failure in one system can cause a cascade of failures across multiple systems, bringing business to a standstill. The project aims to create new technologies to automate the provisioning of virtual deployment environments to test the enterprise systems. In particular, it aims to develop new methods for the automatic analysis of service interaction traces and the generation of accurate executable service models, without requiring explicit knowledge of them. The automatic analysis and generation should reduce development cost for enterprise IT systems and increase system quality and reliability. The new software deployment technologies from this project aim to significantly reduce the time, effort and cost of system quality assurance activities in software development organisations, and yet produce higher-quality software leading to uninterrupted business operation in end-user organisations across all sectors.Read moreRead less
Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar ....Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.Read moreRead less