Analysis and classification of malicious code. Malicious software such as viruses and worms directly attacks the security, privacy and integrity of Australian e-commerce, large databases and communication channels. The recent uptake of malicious software by organised crime has made finding effective countermeasures more urgent. Around 80% of the malicious code in circulation is disguised in some way. This significantly increases the difficulty of automated detection and delays analysis. Automate ....Analysis and classification of malicious code. Malicious software such as viruses and worms directly attacks the security, privacy and integrity of Australian e-commerce, large databases and communication channels. The recent uptake of malicious software by organised crime has made finding effective countermeasures more urgent. Around 80% of the malicious code in circulation is disguised in some way. This significantly increases the difficulty of automated detection and delays analysis. Automated classification and de-obfuscation technologies are a precondition to applying more sophisticated detection heuristics. The project will be instrumental in safeguarding Australia by protecting critical infrastructure and defending us from online organised crime and information warfare.Read moreRead less
Algebraic Properties of Cryptographic Components and their Cryptanalysis. The outcomes will enhance information and communication security, which is absolutely crucial for the rapidly growing e-commerce and e-government services in Australia. International collaboration will be strengthened by reciprocal exchange of researchers and postgraduate students leading to more attractive and productive research environment. Our project will help to maintain a high profile of Australian researchers, to i ....Algebraic Properties of Cryptographic Components and their Cryptanalysis. The outcomes will enhance information and communication security, which is absolutely crucial for the rapidly growing e-commerce and e-government services in Australia. International collaboration will be strengthened by reciprocal exchange of researchers and postgraduate students leading to more attractive and productive research environment. Our project will help to maintain a high profile of Australian researchers, to increase the capacity for consultancy and contract work, and provide a cutting-edge information technology for the Australian telecommunications industry, business and government.Read moreRead less
Efficient pooling of cross-section and time series data using Bayesian machine learning with two econometric applications. In this project, we adapt a Bayesian modelling strategy, namely the minimum message length principle, to the problem of efficient partitioning of economic units, such as firms or countries, into groups whose behavioural patterns are similar within each group but distinct across groups. This methodology can incorporate the requirements of economic theory. The resulting softwa ....Efficient pooling of cross-section and time series data using Bayesian machine learning with two econometric applications. In this project, we adapt a Bayesian modelling strategy, namely the minimum message length principle, to the problem of efficient partitioning of economic units, such as firms or countries, into groups whose behavioural patterns are similar within each group but distinct across groups. This methodology can incorporate the requirements of economic theory. The resulting software will be developed for the Web. We consider two specific applications, namely modelling gasoline demand in OECD countries, and finding the foreign factor with the most predictive power for the growth rate of the Australian economy. The second application is of considerable national interest.Read moreRead less
Computational Intelligence Methods for Financial Applications. Complex financial problems can be better addressed with software that can learn from available data and adapt to environmental changes. It is therefore essential to develop technologies that enable prediction and optimisation in constrained and dynamic environments. There are currently some limitations in existing business decision support systems despite their ubiquity providing an opportunity for Australia to be at the forefront as ....Computational Intelligence Methods for Financial Applications. Complex financial problems can be better addressed with software that can learn from available data and adapt to environmental changes. It is therefore essential to develop technologies that enable prediction and optimisation in constrained and dynamic environments. There are currently some limitations in existing business decision support systems despite their ubiquity providing an opportunity for Australia to be at the forefront as new standards in the field are developed. Furthermore, the fund management industry (particularly superannuation) is significant to the Australian economy and development of this technology has the potential to enhance its performance and reputation.Read moreRead less
Automatic detection of the circle of Willis in neuro-images using multi-scale gradient calculation and knowledge-based genetic algorithms. Stroke is the third most common cause of death and a major contributor to long term disability in Australia. The most efficient way of preventing stroke from happening is to detect related symptoms early. The group of cerebral blood vessels that closely related to strokes is the circle of Willis (CoW). We build a system that can automatically detect and quan ....Automatic detection of the circle of Willis in neuro-images using multi-scale gradient calculation and knowledge-based genetic algorithms. Stroke is the third most common cause of death and a major contributor to long term disability in Australia. The most efficient way of preventing stroke from happening is to detect related symptoms early. The group of cerebral blood vessels that closely related to strokes is the circle of Willis (CoW). We build a system that can automatically detect and quantify CoW in neuroimages, providing ways of preventing strokes from happening. The project will enhance Australia¡¯s leading position in promoting and maintaining good health, especially in preventive healthcare.Read moreRead less
Development of an Integrated Platform for Performance-Based Safety Assessment. Building fires are the cause of major fatalities and injuries amongst all types of accidental fires in Australia. With significant advancement in numerical simulation technique, computer models are becoming acceptable tools for fire safety designs. Nonetheless, these methods still suffer from large amount of manual inputs and lengthy computational times. This research project will address the prevalent deficiency in m ....Development of an Integrated Platform for Performance-Based Safety Assessment. Building fires are the cause of major fatalities and injuries amongst all types of accidental fires in Australia. With significant advancement in numerical simulation technique, computer models are becoming acceptable tools for fire safety designs. Nonetheless, these methods still suffer from large amount of manual inputs and lengthy computational times. This research project will address the prevalent deficiency in many of these computer models and develop a novel and innovative design methodology. The success of this project will revolutionize the computational tools for the industry realizing a convenient, robust and time-saving integrated platform catering for increasing future market demand.Read moreRead less
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less
The Next Step in Intelligent Decision-Support Systems (IDSS): Systems that Learn and Adapt. This project will benefit Australia's scientific knowledge and technology base in the areas of evolutionary computation, business intelligence, and decision management. The outcomes will advance Australian companies and organisations, as many common yet complex business problems can be better addressed with systems that automatically learn and adapt to environmental changes. Such complex business problems ....The Next Step in Intelligent Decision-Support Systems (IDSS): Systems that Learn and Adapt. This project will benefit Australia's scientific knowledge and technology base in the areas of evolutionary computation, business intelligence, and decision management. The outcomes will advance Australian companies and organisations, as many common yet complex business problems can be better addressed with systems that automatically learn and adapt to environmental changes. Such complex business problems include dynamic scheduling (in the manufacturing sector), resource allocation optimisation (in the defence, mining, and agriculture sectors), and network design optimisation (in the telecommunications and energy sectors).Read moreRead less
Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discove ....Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.
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A Comprehensive Platform for Dynamic Decision Support in Warning Systems through Better Management of Uncertain Information. Public and individual warning systems are installed widely in Australia for emergency situations such as fire, terrorist attack, tsunami, and financial risk. The developed platform with its uncertain information management and dynamic decision support software will directly assist Australian government agencies, industries, and professional officers responsible for public ....A Comprehensive Platform for Dynamic Decision Support in Warning Systems through Better Management of Uncertain Information. Public and individual warning systems are installed widely in Australia for emergency situations such as fire, terrorist attack, tsunami, and financial risk. The developed platform with its uncertain information management and dynamic decision support software will directly assist Australian government agencies, industries, and professional officers responsible for public warning systems by improving the reliability of generated warnings, effective design of any new warning system, and accurate decision making in responding threats. It will also greatly contribute to the processing of uncertain information in other organizational information systems, and enhance training exercise facilities in complex emergency environments.Read moreRead less