Brain-skull interface: discovering the missing piece of head biomechanics. Overall objective of this project is to measure, mathematically describe and implement in software mechanical properties of brain-skull interface – a critical component of current large and sophisticated computational models of the brain and the last missing piece of brain biomechanics knowledge. This will allow increased reliability of comprehensive biomechanical models used to simulate realistic injury and surgery scena ....Brain-skull interface: discovering the missing piece of head biomechanics. Overall objective of this project is to measure, mathematically describe and implement in software mechanical properties of brain-skull interface – a critical component of current large and sophisticated computational models of the brain and the last missing piece of brain biomechanics knowledge. This will allow increased reliability of comprehensive biomechanical models used to simulate realistic injury and surgery scenarios.
The problem is significant and urgent. Every year in Australia, there are over 22,000 cases of traumatic brain injury, some of which could be prevented by better passive and active countermeasures; and over 12,000 neurosurgical procedures that surgical simulation could make more accurate and therefore safer.Read moreRead less
3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environmen ....3D Diffusion Models for Generating and Understanding 3D Scenes. Diffusion models, such as DALL-E2 and Imagen, have achieved remarkable success in generating photorealistic images and hold promise to solve long-standing computer vision problems. However, 3D scene generation remains unexplored. This research project aims to bridge the gap by developing 3D diffusion models capable of generating complete 3D scenes. This will advance our theoretical understanding of diffusion in complex 3D environments and open up new possibilities for applications in fields such as virtual reality, architecture, and city planning. The proposed 3D diffusion models will also enhance the accuracy of computer vision tasks related to 3D scene understanding, such as object detection, tracking, and semantic segmentation.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not o ....Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not only practical solutions for protecting sensitive data recorded in blockchain but also crucial techniques to make the blockchain accountable for practical applications with enhanced security. This project provides significant benefits, such as building a trusted environment for sensitive transactions in the digital economy.Read moreRead less
Preventing sensitive data exfiltration from insiders . Confidential data such as military secrets or intellectual property must never be disclosed outside the organisation; formally protecting data exfiltration from insider attacks is a major challenge. This project aims to develop a pattern matching based systematic methodology for data exfiltration in database systems. We will devise highly accurate detection tools and secure provenance techniques that can effectively protect against insider a ....Preventing sensitive data exfiltration from insiders . Confidential data such as military secrets or intellectual property must never be disclosed outside the organisation; formally protecting data exfiltration from insider attacks is a major challenge. This project aims to develop a pattern matching based systematic methodology for data exfiltration in database systems. We will devise highly accurate detection tools and secure provenance techniques that can effectively protect against insider attacks. The outcomes of the project will incorporate new security constraints and policies raised by emerging technologies to enable better protection of sensitive information. Read moreRead less
Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and w ....Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and will create new knowledge to harness the full potential of crowd sourced data curation. This is expected to make a significant benefit towards enhanced organisational capacity to accelerate the time-to-value from data analytics projects.Read moreRead less
Mapping the Effectiveness of Automated Software Testing. This project aims to help software engineers build complex software systems in far more reliable and cost-effective ways. It takes an interdisciplinary approach by applying machine learning techniques to automatically test complex software systems. Expected outcomes include a novel methodology for assessing the strengths and weaknesses of test suites generated by automated software testing techniques and the approaches required for generat ....Mapping the Effectiveness of Automated Software Testing. This project aims to help software engineers build complex software systems in far more reliable and cost-effective ways. It takes an interdisciplinary approach by applying machine learning techniques to automatically test complex software systems. Expected outcomes include a novel methodology for assessing the strengths and weaknesses of test suites generated by automated software testing techniques and the approaches required for generating high-quality test cases. Such advances are urgently needed to avoid disasters when deploying software systems in the real world.Read moreRead less
New methods for drug discovery by NMR spectroscopy. This project aims to advance nuclear magnetic resonance (NMR) spectroscopy methods in the field of drug discovery. It addresses a long-standing bottleneck for medicinal chemists in drug development: the rapid determination of how ligand molecules bind to proteins, where they bind and their orientation in the binding site. The methods include techniques for the attachment of NMR tags to ligands and target proteins, installation of new unnatural ....New methods for drug discovery by NMR spectroscopy. This project aims to advance nuclear magnetic resonance (NMR) spectroscopy methods in the field of drug discovery. It addresses a long-standing bottleneck for medicinal chemists in drug development: the rapid determination of how ligand molecules bind to proteins, where they bind and their orientation in the binding site. The methods include techniques for the attachment of NMR tags to ligands and target proteins, installation of new unnatural amino acids in proteins, and software for automated assignment of NMR spectra and 3D structure modelling of proteins using sparse distance restraints measured by electron paramagnetic resonance (EPR) spectroscopy. The outcome is to benefit the early stages of drug discovery in the biotech industries.Read moreRead less
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.Read moreRead less
Encrypted, Distributed, and Queryable Data Store: Framework and Realisation. This project aims to design an encrypted, distributed, and queryable data store. Distributed data stores are used for a broad spectrum of applications. While creating unprecedented opportunities, long-standing data security and privacy concerns are yet to be tackled. This project expects to propose a new architecture for encrypted data stores, and devise practical query processing functions over encrypted and distribute ....Encrypted, Distributed, and Queryable Data Store: Framework and Realisation. This project aims to design an encrypted, distributed, and queryable data store. Distributed data stores are used for a broad spectrum of applications. While creating unprecedented opportunities, long-standing data security and privacy concerns are yet to be tackled. This project expects to propose a new architecture for encrypted data stores, and devise practical query processing functions over encrypted and distributed data records. The intended outcome should bring users confidence for the secure adoption of cloud data storage services and significantly benefit enterprises that demand guaranteed protection on their proprietary data.Read moreRead less