Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods an ....Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods and efficient algorithms that will be able to prevent real-time exfiltration and identify previously undetected exfiltration of sensitive data. This should provide significant benefits to governments, defence networks as well as businesses and health sectors, as it will protect them from sophisticated cyber attacks.
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Blind separation of mutually correlated sources. This project is aimed at developing novel techniques for blind separation of mutually correlated sources. The expected outcomes will significantly advance the theory of blind source separation and improve the performance of important practical systems, such as densely deployed sensor networks and wireless video surveillance systems.
Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less
New channel estimation, tracking and equalization algorithms for real-time high-speed underwater acoustic communication systems. High-speed underwater communication is vitally important for Australian offshore oil and gas industries, marine commercial operations, and defence applications. However, due to the challenges posed by the harsh underwater channel, current underwater communication systems have significant limitations on data rate and bit-error-rate for many applications and environments ....New channel estimation, tracking and equalization algorithms for real-time high-speed underwater acoustic communication systems. High-speed underwater communication is vitally important for Australian offshore oil and gas industries, marine commercial operations, and defence applications. However, due to the challenges posed by the harsh underwater channel, current underwater communication systems have significant limitations on data rate and bit-error-rate for many applications and environments. This project aims to develop a real-time signal processing platform for reliable high-speed communication through the extremely bandlimited and reverberant underwater acoustic channel. New channel estimation, tracking and equalisation algorithms developed in this project will significantly enhance the capacity of underwater communication systems.Read moreRead less
Increasing the range and rate of underwater acoustic communication systems using multi-hop relay. Australia has a very long coastline, thus it is vitally important for Australia to efficiently explore and exploit the rich resources in the ocean. This project develops novel communication technologies for long-range and high-rate underwater acoustic communications that are crucial to Australian ocean-related industries and defence applications.
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Strategic evaluation model for business-to-business electronic marketplace participation. Striving to become a knowledge-based nation is dependent upon the effective adoption, diffusion and implementation of ICT throughout the business community. The developing world markets, brought about by e-commerce and the increased ability to trade globally facilitated by e-markets, have created significant opportunities for Australian organisations. This research will produce a dynamic model that can be ....Strategic evaluation model for business-to-business electronic marketplace participation. Striving to become a knowledge-based nation is dependent upon the effective adoption, diffusion and implementation of ICT throughout the business community. The developing world markets, brought about by e-commerce and the increased ability to trade globally facilitated by e-markets, have created significant opportunities for Australian organisations. This research will produce a dynamic model that can be used to not only evaluate e-marketplace participation but a wide range of Internet applications. The research will provide Australian managers with the foundation of knowledge needed to guide and support their decision-making when implementing new technology.Read moreRead less
Dynamic Life Cycle Evaluation of Customer Relationship Management Systems. Striving to become a knowledge based nation is dependent upon effective adoption, diffusion and implementation of information and communication technology thoughout the business community. This research will produce a dynamic model that can be used to evaluate enterprise wide applications such as electronic Customer Relationship Management (CRM) so that managers can examine the impact of new tehnology on business processe ....Dynamic Life Cycle Evaluation of Customer Relationship Management Systems. Striving to become a knowledge based nation is dependent upon effective adoption, diffusion and implementation of information and communication technology thoughout the business community. This research will produce a dynamic model that can be used to evaluate enterprise wide applications such as electronic Customer Relationship Management (CRM) so that managers can examine the impact of new tehnology on business processes. In addition, the research will provide managers wit the foundation of knowledge needed to guide and support their decision-making when implementing new technology. Read moreRead less
Private Health Insurance and Utilisation of Health Care in Australia. The breakdown of activity between the Australian public and private health sectors is currently subject to considerable scrutiny. The combination of a comprehensive public system with minimal co-payments, but considerable waiting times for some treatment, and a private system with minimal waiting but sizeable co-payments has interesting economic implications for both consumer and provider behaviour. This research project will ....Private Health Insurance and Utilisation of Health Care in Australia. The breakdown of activity between the Australian public and private health sectors is currently subject to considerable scrutiny. The combination of a comprehensive public system with minimal co-payments, but considerable waiting times for some treatment, and a private system with minimal waiting but sizeable co-payments has interesting economic implications for both consumer and provider behaviour. This research project will explore the relationship between insurance status and utilisation of health care in Australia. Because insurance reduces the out-of-pocket price for consumers, they tend to purchase more care than they would without insurance.Read moreRead less
Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord ....Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.Read moreRead less