Effective and efficient protection of personal privacy in big personal data. Personal privacy protection is becoming increasingly important as personal data is increasingly being hosted in cloud servers, accumulating as big personal data. This project aims to develop innovative solutions for effective and efficient to address the issue of protection of personal privacy. Current approaches are neither effective nor efficient, and lack robustness. The project is expected to enhance theoretical fou ....Effective and efficient protection of personal privacy in big personal data. Personal privacy protection is becoming increasingly important as personal data is increasingly being hosted in cloud servers, accumulating as big personal data. This project aims to develop innovative solutions for effective and efficient to address the issue of protection of personal privacy. Current approaches are neither effective nor efficient, and lack robustness. The project is expected to enhance theoretical foundation of personal privacy protection in big data and cloud, and deliver an effective and efficient personal privacy protection framework with associated algorithms and prototype. These outcomes will help to protect fast-growing privacy sensitive personal data hosting and applications on cloud servers.Read moreRead less
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
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
Learning the Focus of Attention to Detect Distributed Coordinated Attacks. Cyber security analysts need to detect and respond to attacks as soon as possible, to minimise the damage attackers can inflict. However, the growth in highly distributed attacks that span multiple networks has meant that massive volumes of data need to be analysed. While machine learning techniques can help filter the data, we need techniques that can automatically provide a focus of attention for analysts on the most re ....Learning the Focus of Attention to Detect Distributed Coordinated Attacks. Cyber security analysts need to detect and respond to attacks as soon as possible, to minimise the damage attackers can inflict. However, the growth in highly distributed attacks that span multiple networks has meant that massive volumes of data need to be analysed. While machine learning techniques can help filter the data, we need techniques that can automatically provide a focus of attention for analysts on the most relevant observations. Our aim is to devise a novel suite of attention mechanisms that can focus the search of machine learning techniques for cyber security. The results of this project will improve the accuracy and efficiency of detecting distributed attacks across multiple networks.Read moreRead less
Sentient buildings. This project aims to unite outputs from the large and varied array of sensors deployed in buildings into a coherent whole. By coordinating detections of resources and personnel from multiple sensors, it intends to enable more efficient allocation of shared resources within a public site such as a hospital, and enable a more effective emergency response. It intends to also allow the building to adapt over time to the way it is used, or to changing conditions. This is expected ....Sentient buildings. This project aims to unite outputs from the large and varied array of sensors deployed in buildings into a coherent whole. By coordinating detections of resources and personnel from multiple sensors, it intends to enable more efficient allocation of shared resources within a public site such as a hospital, and enable a more effective emergency response. It intends to also allow the building to adapt over time to the way it is used, or to changing conditions. This is expected to benefit the Australian construction industry as well as building operators, giving them a valuable export commodity. It intends also to benefit inhabitants of the buildings by providing a more safe, secure and accommodating environment.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE180100158
Funder
Australian Research Council
Funding Amount
$348,026.00
Summary
A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and ....A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and evaluation of IoT technologies and services. The project will also serve as a vehicle for the education and training of Australia’s next generation of scholars and engineers, and contribute to Australia’s scientific visibility.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100679
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and effic ....Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and efficiently support a set of primitive queries including rank-based queries, dominance-based queries and proximity-based queries. The results of this project will be an important complement to the development of data stream systems and will bring considerable social, economic and technological benefits to Australia.Read moreRead less
Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database i ....Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database indexing, event-influenced behaviour modelling and prediction. The success of this project is expected to enhance users’ online experience and improve e-commerce’s market value.Read moreRead less
Taming the uncertainty in trajectory data. This project aims to develop effective and efficient methods to manage large scale uncertain trajectory data. It provides individuals, business, government and social groups the ability to explore significant uncertain trajectories and their patterns, for important usages in location based services, logistic, transportation and tourism.