DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less
Using data mining methods to remove uncertainties in sensor data streams. This project will develop key techniques for removing uncertainties in sensor data streams and thus improve the monitoring quality of sensor networks. The expected outcomes will benefit Australia by enabling improved, lower-cost monitoring of natural resources and management of stock raising.
Manoeuvrable burrowing robots for underground search. It is very difficult to locate items that have been buried underground or to find out their condition without digging them up. There are a number of situations involving leaking underground chemical storage tanks, and pipelines together with improperly disposed of chemical containers where chemical leaks can pose dangers to the environment and human health. This project aims to develop a robotic system that can burrow through the ground and h ....Manoeuvrable burrowing robots for underground search. It is very difficult to locate items that have been buried underground or to find out their condition without digging them up. There are a number of situations involving leaking underground chemical storage tanks, and pipelines together with improperly disposed of chemical containers where chemical leaks can pose dangers to the environment and human health. This project aims to develop a robotic system that can burrow through the ground and home in on sources of leaking chemicals. Such a system could pinpoint the sources of leaks without requiring extensive excavations.Read moreRead less
Robust Intelligence: Rational Decision-Making under Risk and Uncertainty. This project seeks to bridge the gap between theory and practice with an innovative framework for rational decision-making under risk and uncertainty. Intelligent agents exercise profound and growing impact in business and society. However, significant problems arise in intelligent agent deployment as their theoretical underpinnings do not ensure rational decision-making in complex real-world settings. The project aims to ....Robust Intelligence: Rational Decision-Making under Risk and Uncertainty. This project seeks to bridge the gap between theory and practice with an innovative framework for rational decision-making under risk and uncertainty. Intelligent agents exercise profound and growing impact in business and society. However, significant problems arise in intelligent agent deployment as their theoretical underpinnings do not ensure rational decision-making in complex real-world settings. The project aims to open the door to transformational technologies that may drive new entrepreneurial opportunities in agent-based global services.Read moreRead less
Accurate analysis of combinatorial problems: from the particular to the general. Combinatorial problems pervade all aspects of our social, environmental and economic life, but finding good solutions to these problems can take too much computer time. This project will develop new analysis tools that are effective at reducing this time, thus allowing for better solutions to be found.
Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recogniti ....Taming media for the masses: Computational frameworks for intelligent digital media capture, management, and sharing. The core issues tackled in this project are learning, recognition and application of semantics in multimedia data and the context of its creation and use - a foundational issue in pattern recognition with many applications. The project is part of the Institute for Multi-sensor Processing and Content Analysis whose aim is to tackle technical issues in large scale pattern recognition. By developing scalable and robust techniques to extract information from large scale multi-modal data, the applications include large scale surveillance systems from multi-modal data (e.g. airport security, smart homes for the aged), context-aware devices, and the next generation of media creation and repurposing tools - a fast-growing sector of the economy.Read moreRead less
Learning Semi-Naive Bayesian Classifiers from Numeric Data. This project addresses research priority 3, offering frontier technologies. It will deliver better and faster classification technologies that greatly help accomplish many real-world tasks including medical diagnosis, fraud detection, spam filtering and webpage search, where accurate and fast classification is critical to save life, increase efficiency, reduce crime and conserve resources. Hence this project addresses priority 4 as well ....Learning Semi-Naive Bayesian Classifiers from Numeric Data. This project addresses research priority 3, offering frontier technologies. It will deliver better and faster classification technologies that greatly help accomplish many real-world tasks including medical diagnosis, fraud detection, spam filtering and webpage search, where accurate and fast classification is critical to save life, increase efficiency, reduce crime and conserve resources. Hence this project addresses priority 4 as well, better safeguarding Australia from disease and crime. This project will also support a young research group of international standing. It will train the involved researchers to attain a high level of proficiency and excellence in machine learning research and development.Read moreRead less
Modelling graph-of-graphs for solving document categorisation problems. Documents in the World Wide Web, such as scientific documents, exhibit a referencing structure as well as being structured objects themselves. This project addresses some inherent limitations of existing modelling techniques in order to improve on the quality of results, and to allow the addressing of some unsolved problems involving documents.
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
Towards automated and intelligent processing of web-based information. The successful outcome of this project will enhance Australia's research reputation in an important, practical area of ICT, will contribute to emerging Web standards, will produce frontier technology that will eventually be of benefit to Australian industry, and will train several postgraduate students.