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
Privacy preserving and data utility in outsourced systems. Making the best tradeoff between data privacy and utility is a vital challenge in privacy-preserving outsourcing environments. This project aims to develop a balanced distributed framework to achieve the best utility of outsourced data while protecting private information. The framework consists of general structure of distributed evolutionary algorithms and a predefined topology for high optimization efficiency and a dynamic groupin ....Privacy preserving and data utility in outsourced systems. Making the best tradeoff between data privacy and utility is a vital challenge in privacy-preserving outsourcing environments. This project aims to develop a balanced distributed framework to achieve the best utility of outsourced data while protecting private information. The framework consists of general structure of distributed evolutionary algorithms and a predefined topology for high optimization efficiency and a dynamic grouping recombination model. The project outcomes will be beneficial to applications in the nation as it incorporates new privacy constraints and utility requirements raised by emerging technologies to enable better protection of sensitive information and maximal data utility in outsourced systems. 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
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. 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
Privacy-Preserving Fog Info System in Infrastructure-Deficient Environments. Due to Australia’s unique geographical distribution and population density, many regional or remote areas lack infrastructural support and development, including telecommunications and electricity supply. It is important to provide information and communication services in such infrastructure-deficient environments. In this project, we will develop a first-ever commercially ready Fog information system, or FogIS in shor ....Privacy-Preserving Fog Info System in Infrastructure-Deficient Environments. Due to Australia’s unique geographical distribution and population density, many regional or remote areas lack infrastructural support and development, including telecommunications and electricity supply. It is important to provide information and communication services in such infrastructure-deficient environments. In this project, we will develop a first-ever commercially ready Fog information system, or FogIS in short, to enable localised information and communication services, while preserving users' privacy, in infrastructure-deficient environments. The deployment of this system will bring great benefits to Australia’s economic growth, the quality of life, cybersecurity, and environment control in rural and regional Australia. Read moreRead less
Intelligent Technologies for Smart Cryptography. This project aims to improve cybersecurity by automating the process of generating cryptographic software for smart devices. The expected outcomes are tools that automatically produce efficient cryptographic software that resists attacks. The main benefit of this project is to reduce the amount of expert labour required when developing secure software.
Discovery Early Career Researcher Award - Grant ID: DE200100016
Funder
Australian Research Council
Funding Amount
$351,798.00
Summary
Enabling Compatible and Secure Mobile Apps via Automated Program Repair. This project aims to ensure everyone in Australia and the world can reliably utilise compatible and secure mobile apps on their smart devices, by inventing a novel approach to automatically fix compatibility and security issues during app development and installation. The project expects to generate new knowledge, tools and methods to support efficient mobile app fix through mining the best practices from the mobile ecosyst ....Enabling Compatible and Secure Mobile Apps via Automated Program Repair. This project aims to ensure everyone in Australia and the world can reliably utilise compatible and secure mobile apps on their smart devices, by inventing a novel approach to automatically fix compatibility and security issues during app development and installation. The project expects to generate new knowledge, tools and methods to support efficient mobile app fix through mining the best practices from the mobile ecosystem. Expected outcomes include better support for app developers to build mobile apps that will maximise the potential of the mobile ecosystem for Australian businesses. This should provide significant benefits, such as enhanced productivity for the software industry and better mobile app experience and safety for users.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100166
Funder
Australian Research Council
Funding Amount
$424,709.00
Summary
Enabling Energy Self-Sufficient and Secure Internet of Things. This project aims to develop novel resource management and transmission techniques to enable an energy self-sufficient and secure Internet of Things by utilising energy harvesting technology and robust physical-layer security approach. This project expects to generate new knowledge to address current challenges around energy self-sufficiency and data confidentiality protection capabilities. Expected outcomes include efficient algorit ....Enabling Energy Self-Sufficient and Secure Internet of Things. This project aims to develop novel resource management and transmission techniques to enable an energy self-sufficient and secure Internet of Things by utilising energy harvesting technology and robust physical-layer security approach. This project expects to generate new knowledge to address current challenges around energy self-sufficiency and data confidentiality protection capabilities. Expected outcomes include efficient algorithms and prototypes for long-lasting Internet of Things systems. This should provide significant benefits, including the improved self-sustainability and security critical to realising the Internet of Things’ potential to contribute to enhanced health service delivery and factory automation for Industry 4.0.Read moreRead less
Embedding Enterprise Systems in IoT Fog Networks through Microservices. The project will enable automated re-engineering of enterprise systems, to allow them to reused in Internet-of-Things (IoT) applications. It will support efficient ways in which the core business logic of these large scale and monolithic systems can be extended into resource control and data sensing functions managed through the IoT. The project will develop a novel, fine-grained software architecture style suitable for loca ....Embedding Enterprise Systems in IoT Fog Networks through Microservices. The project will enable automated re-engineering of enterprise systems, to allow them to reused in Internet-of-Things (IoT) applications. It will support efficient ways in which the core business logic of these large scale and monolithic systems can be extended into resource control and data sensing functions managed through the IoT. The project will develop a novel, fine-grained software architecture style suitable for localised IoT execution, through microservices executing autonomously on nodes of IoT fog networks. It will develop new techniques for automated discovery of microservices from enterprise systems and the verification of future-state system execution based on current-state behavioural and other properties such as security.Read moreRead less