A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise th ....A Data-Centric Mobile Edge Platform for Resilient Logistics & Supply Chain. This project aims to develop a secure mobile edge computing platform for resilient logistic and supply chain management. It consists of easy-used functions that help businesses realise low latency, high reliability, low cost, and high security in their logistics and supply chain system. To cope with the vast generated application data, we invent new data replication, placement, and deduplication techniques to optimise the mobile edge computing platform from the computation, storage, and network aspects. The invented mobile edge computing platform will enable more intelligent business applications for various industries, e.g., IT, manufacturing, and media, to appear, thus benefiting both the economy of Australia.Read moreRead less
Cost-effective and Reliable Edge Caching for Software Vendors. This project aims to deliver a suite of models and techniques for cost-effective and reliable data caching in the multi-access edge computing (MEC) environment facilitated by 5G mobile network. MEC offers great promises for rapidly advancing mobile and IoT applications in various domains in Australia, e.g., smart cities, remote medical services, advanced manufacturing, etc. Combining graph analytics, optimisation techniques and game ....Cost-effective and Reliable Edge Caching for Software Vendors. This project aims to deliver a suite of models and techniques for cost-effective and reliable data caching in the multi-access edge computing (MEC) environment facilitated by 5G mobile network. MEC offers great promises for rapidly advancing mobile and IoT applications in various domains in Australia, e.g., smart cities, remote medical services, advanced manufacturing, etc. Combining graph analytics, optimisation techniques and game theory, this project tackles the new challenges in the placement, update and adaptation of edge data faced by software vendors embracing 5G. The outcomes can ease software vendors' cost and security concerns during the transition from 4G to 5G, and significantly promote the wave of 5G innovation in Australia.Read moreRead less
Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less
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
Practical unified framework for secure e-consent mechanism for health records. This project is driven by modern applications of cryptography and network security and their applications in securing e-health by enabling secure Personal Health Records (PHRs), which will play an important role in the future healthcare industry.
RAINBOW - RAdIo Networks Based On machine learning for situation aWareness. This project aims to develop software-defined and cognitive radio networks (SDR) to detect adversarial communications and achieve situation awareness on radio frequency (RF) spectrum. The project will generate novel SDR architectures and new attack-resistant detection algorithms through innovative approaches combining machine learning and game theory. Expected outcomes include a strategic alliance between the University ....RAINBOW - RAdIo Networks Based On machine learning for situation aWareness. This project aims to develop software-defined and cognitive radio networks (SDR) to detect adversarial communications and achieve situation awareness on radio frequency (RF) spectrum. The project will generate novel SDR architectures and new attack-resistant detection algorithms through innovative approaches combining machine learning and game theory. Expected outcomes include a strategic alliance between the University of Melbourne and the Northrop Grumman Corporation. Among significant benefits, the project will improve cybersecurity of RF spectrum as a national asset, help protect critical infrastructure relying on wireless networks such as telecommunications and defence, and build skills in cybersecurity and Artificial Intelligence.Read moreRead less
Development of Cryptographic Library and Support System. The protection of the whole cyber space relies on a foundation of cryptography. Cryptographic components of apps authenticate remote parties and secure the communications. However, cryptographic misuse has become a most common issue in development of security component, affecting up to 90% of apps!
This project aims to research, design and develop a crypto library. The innovation of this project lays in three aspects: (1) we will develop ....Development of Cryptographic Library and Support System. The protection of the whole cyber space relies on a foundation of cryptography. Cryptographic components of apps authenticate remote parties and secure the communications. However, cryptographic misuse has become a most common issue in development of security component, affecting up to 90% of apps!
This project aims to research, design and develop a crypto library. The innovation of this project lays in three aspects: (1) we will develop a self-contained, reliable, compatible and verifiable crypto library; (2) we will develop security test software automatically to test and verify security of codes; and (3) we will provide intelligent decision support through argumentation to help developers to apply the library efficiently and correctly.Read moreRead less
Advancing vegetation classification and mapping to meet conservation needs. The project aims to develop advanced statistical and modelling techniques to classify and map vegetation over very large areas, using the most extensive and detailed vegetation data set in Australia and new methods to evaluate these classifications. Such classifications and maps provide the data needed to make biodiversity conservation decisions, yet current operational methods are limited over very large areas, and cann ....Advancing vegetation classification and mapping to meet conservation needs. The project aims to develop advanced statistical and modelling techniques to classify and map vegetation over very large areas, using the most extensive and detailed vegetation data set in Australia and new methods to evaluate these classifications. Such classifications and maps provide the data needed to make biodiversity conservation decisions, yet current operational methods are limited over very large areas, and cannot deal with varied sources of uncertainty. Expected outcomes and benefits include a fine-scale vegetation classification and map for almost a million square kilometres, and associated analytical tools and guidelines for large-scale vegetation classification and global mapping.Read moreRead less
Smart passive sampling of heavy metals in aquatic systems. Smart passive sampling of heavy metals in aquatic systems. This project aims to construct smart devices with extracting polymeric membranes for advanced passive sampling of heavy metal ions. These devices should improve the passive sampling of pollutants such as heavy metals by overcoming the effect of the variability of water temperature, composition and velocity during sampling, which substantially reduces the reliability of analytical ....Smart passive sampling of heavy metals in aquatic systems. Smart passive sampling of heavy metals in aquatic systems. This project aims to construct smart devices with extracting polymeric membranes for advanced passive sampling of heavy metal ions. These devices should improve the passive sampling of pollutants such as heavy metals by overcoming the effect of the variability of water temperature, composition and velocity during sampling, which substantially reduces the reliability of analytical data. These devices are expected to reliably identify sources of heavy metal pollution in urban municipal wastewaters and stormwaters without the need for labour intensive monitoring operations, thus saving considerable time and expense to the Australian water industry.Read moreRead less
Deep mining neurological abnormalities from brain signal data. This project aims to develop a reliable, robust and real-time analysis system for automatic and accurate detection of neurological abnormalities, and the prediction of impending neurological problems from brain signal data. The project expects to design novel algorithms for brain signal processing, data compression, and detection and prediction of neurological abnormalities from massive brain signal data. The project will lead to sig ....Deep mining neurological abnormalities from brain signal data. This project aims to develop a reliable, robust and real-time analysis system for automatic and accurate detection of neurological abnormalities, and the prediction of impending neurological problems from brain signal data. The project expects to design novel algorithms for brain signal processing, data compression, and detection and prediction of neurological abnormalities from massive brain signal data. The project will lead to significant improvement of existing methods in health monitoring applications in Australia and worldwide and hence will save lives, money and resources.Read moreRead less