Discovery Early Career Researcher Award - Grant ID: DE210100019
Funder
Australian Research Council
Funding Amount
$408,000.00
Summary
A Scalable and Adaptive-Resilient Blockchain. This project aims to address the security and scalability challenges that limit blockchain adoption. Existing blockchains do not scale and are vulnerable to attacks (e.g. with a total loss of over US$1 billion in 2019). This project expects to improve security by adaptively enforcing the currently broken security assumptions, and to improve scalability by designing blockchains with high concurrency via relaxed criteria on the ordering of transactions ....A Scalable and Adaptive-Resilient Blockchain. This project aims to address the security and scalability challenges that limit blockchain adoption. Existing blockchains do not scale and are vulnerable to attacks (e.g. with a total loss of over US$1 billion in 2019). This project expects to improve security by adaptively enforcing the currently broken security assumptions, and to improve scalability by designing blockchains with high concurrency via relaxed criteria on the ordering of transactions. The expected outcomes include foundations and practical solutions for self-adaptive, secure and scalable blockchains. The benefits of this would be improved confidence in and capacity for building blockchain applications, which have a predicted value of over US$3.1 trillion by 2030.Read moreRead less
Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges ....Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges and expects to establish innovative research and solutions for enabling full lifecycle privacy protection on cloud. The project outcomes will help to safeguard Australian community in fast-growing online cyber world, and benefit to fast-growing privacy sensitive data hosting and applications on cloud.Read moreRead less
Privacy-preserving online user matching. This project aims to develop efficient techniques to preserve the privacy of users of online matching websites used for finding employment, friends and partners. The project expects to generate new knowledge in privacy preserving user matching with multiple servers. The expected outcomes are new techniques that can find matching users without revealing their interests to the matching server and a prototype based on these techniques. This should alleviate ....Privacy-preserving online user matching. This project aims to develop efficient techniques to preserve the privacy of users of online matching websites used for finding employment, friends and partners. The project expects to generate new knowledge in privacy preserving user matching with multiple servers. The expected outcomes are new techniques that can find matching users without revealing their interests to the matching server and a prototype based on these techniques. This should alleviate the privacy concerns of people using online tools that require providing personal information.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
Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to p ....Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to provide these languages with improved memory-management algorithms, and provides researchers and industry with a framework for innovation. This project will enable safe software that is more efficient on today's hardware and able to exploit emerging hardware. This project should lead to better performance and energy savings for server applications, phones, watches, and smart appliances, while ensuring memory safety.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.Read moreRead less
Private searching on streaming data. This project aims to explore secure and practical solutions for various internet search types and to develop a prototype of a private searching system to avoid compromising user privacy whilst sharing query requests. Searching of streaming data allows collection of useful information from huge streaming sources of data such as on-line news feeds and internet chat-rooms. Current solutions for this problem are inefficient and restricted to a couple of simple se ....Private searching on streaming data. This project aims to explore secure and practical solutions for various internet search types and to develop a prototype of a private searching system to avoid compromising user privacy whilst sharing query requests. Searching of streaming data allows collection of useful information from huge streaming sources of data such as on-line news feeds and internet chat-rooms. Current solutions for this problem are inefficient and restricted to a couple of simple search types, and vulnerable to identifying the search requester. The project expects to develop private searching tools to protect the privacy of user's search queries. This will have the potential to detect any attacks to our digital infrastructure while keeping the search criteria classified, and could have applications in Australian counter-terrorism and homeland defence.Read moreRead less
Intelligent Incident Management for Software-Intensive Systems. This project aims to develop intelligent incident management methods for software-intensive systems. Incidents are unplanned system interruptions or outages that could affect the normal operations of an organization and cause huge economic loss. This project expects to develop innovative, Artificial Intelligence (AI) based methods for automated incident management, including incident detection, incident identification, and incident ....Intelligent Incident Management for Software-Intensive Systems. This project aims to develop intelligent incident management methods for software-intensive systems. Incidents are unplanned system interruptions or outages that could affect the normal operations of an organization and cause huge economic loss. This project expects to develop innovative, Artificial Intelligence (AI) based methods for automated incident management, including incident detection, incident identification, and incident triage. Expected outcomes of the project include a set of novel methods and tools that can facilitate incident diagnosis and resolution. This project will provide significant benefits, such as improving the availability of software-intensive systems and reducing the economic loss caused by the incidents. 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
The right to be forgotten: GDPR modelling in cross-domain social networks . The project aims to develop a theoretical model and practical mechanisms to address the critical challenge – ‘right to be forgotten’ - raised from the General Data Protection Regulation (GDPR) with minimal compromising of the utility of the data. To achieve the aim, we will design a ‘right to be forgotten’ framework and associated erasure mechanisms that are effective even information is derived from multiple related soc ....The right to be forgotten: GDPR modelling in cross-domain social networks . The project aims to develop a theoretical model and practical mechanisms to address the critical challenge – ‘right to be forgotten’ - raised from the General Data Protection Regulation (GDPR) with minimal compromising of the utility of the data. To achieve the aim, we will design a ‘right to be forgotten’ framework and associated erasure mechanisms that are effective even information is derived from multiple related social networks. The framework will be created by identifying heterogeneous information, modelling individual behaviour patterns and designing erasure policies. The outcomes of the project can be used by the government to provide privacy guarantees to Australian cyberspace and by industry to protect their clients’ privacy.Read moreRead less