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
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
Discovery Early Career Researcher Award - Grant ID: DE180100153
Funder
Australian Research Council
Funding Amount
$361,446.00
Summary
Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to impr ....Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to improve project awareness, and to increase productivity goals. The outcomes would include a comprehensive decision and awareness support system for software projects, based on automating the creation and continual updating of developer activity summaries and measures.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100941
Funder
Australian Research Council
Funding Amount
$392,778.00
Summary
Practical and Explainable Analytics to Prevent Future Software Defects. This project aims to create technologies that enable software engineers to produce the highest quality software systems with the lowest costs, by preventing future defects in safety-critical systems that could result in death and disasters. Expected outcomes of this project include new theories, techniques, and analytics systems to assist software engineers accurately predict, explain, and prevent future software defects bef ....Practical and Explainable Analytics to Prevent Future Software Defects. This project aims to create technologies that enable software engineers to produce the highest quality software systems with the lowest costs, by preventing future defects in safety-critical systems that could result in death and disasters. Expected outcomes of this project include new theories, techniques, and analytics systems to assist software engineers accurately predict, explain, and prevent future software defects before they impact end users. This should provide significant benefits including accelerating the productivity of the software industry while preventing software defects in many critical domains including smart city and e-health applications.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100021
Funder
Australian Research Council
Funding Amount
$413,665.00
Summary
An Intelligent Programmer’s Assistant Using Data Mining. This project aims to advance the important practice of pair programming in software engineering via software repository mining and create automated support tools. This project expects to use innovative techniques combining artificial intelligence, programming analysis and software analytics, to help software developers review code, fix bugs and implement new features. Expected outcomes of this project include an intelligent programmer’s as ....An Intelligent Programmer’s Assistant Using Data Mining. This project aims to advance the important practice of pair programming in software engineering via software repository mining and create automated support tools. This project expects to use innovative techniques combining artificial intelligence, programming analysis and software analytics, to help software developers review code, fix bugs and implement new features. Expected outcomes of this project include an intelligent programmer’s assistant, consisting of a set of automated tools, covering software development, testing and maintenance. This should provide significant benefits to the Australian software development industry by improving developers’ productivity and reduce overall project costs.Read moreRead less
Data-driven Approach to Resilient Online Service Systems. This project aims to develop a data-driven approach to improving the resilience of online service systems. Many software systems are now provided as online services via the Internet on a 24/7 basis. Although a lot of effort has been devoted to service quality assurance, in reality, online service systems still encounter many incidents and fail to satisfy user requests. This project expects to develop innovative data-driven methods for eff ....Data-driven Approach to Resilient Online Service Systems. This project aims to develop a data-driven approach to improving the resilience of online service systems. Many software systems are now provided as online services via the Internet on a 24/7 basis. Although a lot of effort has been devoted to service quality assurance, in reality, online service systems still encounter many incidents and fail to satisfy user requests. This project expects to develop innovative data-driven methods for effective fault identification, fault localization, and failure prediction. Expected outcomes of this project include novel techniques and tools for maintaining online service systems. This project will provide significant benefits, such as improving the resilience and reliability of our cyber infrastructure.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101577
Funder
Australian Research Council
Funding Amount
$427,116.00
Summary
Microarchitectural attacks and JavaScript: threats and defences. This project aims to improve cybersecurity by identifying and mitigating vulnerabilities in Internet-connected computers. Expected outcomes of this project include novel techniques for protecting web browsers and cloud server, to prevent them from inadvertent leaks of private or sensitive information. This should provide significant benefits, such as reduced risk of cyberattacks and improved privacy for web users.
Design and verification of correct, efficient and secure concurrent systems. This project aims to provide methods for the design and verification of correct, secure and efficient concurrent software that are scalable and mechanised. Computers with multiple processors are now the norm and are used in a wide range of safety, security and mission critical software applications such as transport, health and infrastructure. These multi-core architectures have the potential to lead to important effici ....Design and verification of correct, efficient and secure concurrent systems. This project aims to provide methods for the design and verification of correct, secure and efficient concurrent software that are scalable and mechanised. Computers with multiple processors are now the norm and are used in a wide range of safety, security and mission critical software applications such as transport, health and infrastructure. These multi-core architectures have the potential to lead to important efficiency gains, but can introduce complex and error-prone behaviours that cannot be managed using traditional software development approaches. This project will produce better, scalable and mechanised methods for the design and verification of such software which is expected to reduce the prevalence of failures in efficient, modern software.Read moreRead less
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
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.