Natural form, aesthetics and the human brain. This project aims to study how the brain represents the emotion of aesthetic experience. This project will establish the characteristics of flowers and floral design that govern their appeal using large scale web based data collection, and identify the neural representation of floral beauty using integrative data analysis. Outcomes of the project are expected to help flower growers and designers with product planning, supporting industry sustainabili ....Natural form, aesthetics and the human brain. This project aims to study how the brain represents the emotion of aesthetic experience. This project will establish the characteristics of flowers and floral design that govern their appeal using large scale web based data collection, and identify the neural representation of floral beauty using integrative data analysis. Outcomes of the project are expected to help flower growers and designers with product planning, supporting industry sustainability. The project will also establish how the brain generates positive experience in response to our visual environment, promoting well-being by enabling informed visual design decisions.Read moreRead less
Explainable Artificial Creativity. This project aims to develop explainable models for creative AI systems which enable more productive and satisfying interactions between them and their human co-creators. This will boost both human and machine creativity through sustained, ongoing exchanges, leading to high-quality creative outcomes via automated ideation and more advanced human-machine collaborations. The proposed techniques will be validated with creative professionals, ensuring practical ind ....Explainable Artificial Creativity. This project aims to develop explainable models for creative AI systems which enable more productive and satisfying interactions between them and their human co-creators. This will boost both human and machine creativity through sustained, ongoing exchanges, leading to high-quality creative outcomes via automated ideation and more advanced human-machine collaborations. The proposed techniques will be validated with creative professionals, ensuring practical industry relevance. We expect the outcomes to include new methods that automatically generate persuasive explanations, new forms of communication including dialogues between creative AI systems and users, and new understanding of general aspects of explainability for creative AI systems.Read moreRead less
Outsider artists and the reformulation of Australian art. This project aims to produce an understanding of outsider artists, their lives, their histories, and the socio-historic context in which they made their work. “Outsider artists” includes artists experiencing incarceration, disability, mental illness and other forms of marginalisation. Integration of their work will lead to a deeper understanding of mainstream art in Australia to paint a richer, more complex picture of the history of Aust ....Outsider artists and the reformulation of Australian art. This project aims to produce an understanding of outsider artists, their lives, their histories, and the socio-historic context in which they made their work. “Outsider artists” includes artists experiencing incarceration, disability, mental illness and other forms of marginalisation. Integration of their work will lead to a deeper understanding of mainstream art in Australia to paint a richer, more complex picture of the history of Australian art. The project will alter the perspective of arts policy and agencies, and of Australian artists themselves.Read moreRead less
Special Research Initiatives - Grant ID: SR200200052
Funder
Australian Research Council
Funding Amount
$271,000.00
Summary
The war at home: art describes Australia’s turbulent present. This project investigates the friction between the nation’s stories of itself, and the current massive fracturing of health, of places and of peoples. Because Australia is changing beyond measure, it is even appropriate to talk about the war at home. From World War 1 onwards, the Australian government decided that war artists be commissioned to make art about the nation at war. Our project proposes that a team of Australian artists, w ....The war at home: art describes Australia’s turbulent present. This project investigates the friction between the nation’s stories of itself, and the current massive fracturing of health, of places and of peoples. Because Australia is changing beyond measure, it is even appropriate to talk about the war at home. From World War 1 onwards, the Australian government decided that war artists be commissioned to make art about the nation at war. Our project proposes that a team of Australian artists, with a deep experience of picturing conflict, investigates the current war at home, guided by a senior Gunditjimara elder and in collaboration with an eminent biomedical scientist. Future Australians will benefit from the heritage created by art portraying a new understanding of the current war at home.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
The Role of the Creative Arts in Regional Australia: A Social Impact Model. This project will address the challenge to effectively target regional arts funding to programs and activities that build capacity and have lasting impact for end-users. It delivers a framework for evaluating the arts, to argue for the arts to be included in a broader understanding of community and national wellbeing and success. This framework will position Australia as an international leader in articulating and respon ....The Role of the Creative Arts in Regional Australia: A Social Impact Model. This project will address the challenge to effectively target regional arts funding to programs and activities that build capacity and have lasting impact for end-users. It delivers a framework for evaluating the arts, to argue for the arts to be included in a broader understanding of community and national wellbeing and success. This framework will position Australia as an international leader in articulating and responding to the social impact of the arts. The research field sites have been chosen in consultation with our partners as communities whose capacity and challenges are reflected throughout much of regional Australia.Read moreRead less
Defending AI based FinTech Systems against Model Extraction Attacks. This project aims to develop new methods for defending artificial intelligence (AI) based FinTech systems from highly potent and insidious model extraction attacks whereby an adversary can steal the AI model from the system to cause intellectual property (IP) violation, business advantage disruption, and financial loss. This can be achieved by examining various attack models, creating active and utility-preserving defences, and ....Defending AI based FinTech Systems against Model Extraction Attacks. This project aims to develop new methods for defending artificial intelligence (AI) based FinTech systems from highly potent and insidious model extraction attacks whereby an adversary can steal the AI model from the system to cause intellectual property (IP) violation, business advantage disruption, and financial loss. This can be achieved by examining various attack models, creating active and utility-preserving defences, and inventing non-removable watermarks on AI models. The outcomes are new tools for securing AI-based FinTech systems before deployment and tools for IP violation forensics post-deployment. Such capabilities are beneficial by improving the security and safety of FinTech systems and other nationally critical AI systems.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