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
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
Discovery Early Career Researcher Award - Grant ID: DE210101091
Funder
Australian Research Council
Funding Amount
$402,160.00
Summary
Data-Driven Code Reviews for Cost-Effective Software Quality Assurance. This DECRA project aims to create advanced techniques that will enable software engineers to effectively assure the highest quality of software systems with minimal cost through data-driven recommendations. The current standard practices in software quality assurance involve the manual and tedious process of code review, which can lead to high costs and cause severe delays in software development. The expected outcomes of th ....Data-Driven Code Reviews for Cost-Effective Software Quality Assurance. This DECRA project aims to create advanced techniques that will enable software engineers to effectively assure the highest quality of software systems with minimal cost through data-driven recommendations. The current standard practices in software quality assurance involve the manual and tedious process of code review, which can lead to high costs and cause severe delays in software development. The expected outcomes of this project include new theories, techniques, and an automated system that provides insightful feedback, suitable reviewer recommendations, and fine-grained effort prioritisation. Significant benefits are expected to improve the production of Australia's software and the quality of safety-critical software systems.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
Security and Privacy of Individual Data Used to Extract Public Information. The project aims to contribute to the development of techniques to allow the harvesting of useful information without compromising personal privacy. Intelligent analysis of personal data can reveal valuable knowledge about a population but at a risk of invading an individual's privacy. This project aims to provide at least partial solutions to some of the problems associated with the protection of private data. In partic ....Security and Privacy of Individual Data Used to Extract Public Information. The project aims to contribute to the development of techniques to allow the harvesting of useful information without compromising personal privacy. Intelligent analysis of personal data can reveal valuable knowledge about a population but at a risk of invading an individual's privacy. This project aims to provide at least partial solutions to some of the problems associated with the protection of private data. In particular, it plans to work on the problem of security of statistical databases and privacy of streaming data. This would be underpinned by a study of anonymisation and homomorphic encryption. The expected outcomes are new theoretical results, new algorithms and protocols applicable to at least some of the current significant problems in information security.Read moreRead less
An active approach to detect and defend against peer-to-peer botnets. The aim of this project is to develop an effective defence system to help organisations detect and defend against the peer-to-peer (P2P) botnets. If this research is accomplished successfully, it will be a big step forward in defeating this new but devastating malicious software widely utilised by Internet criminals and terrorists. The capability of a nation to defend against the P2P botnet attacks on its information infrastru ....An active approach to detect and defend against peer-to-peer botnets. The aim of this project is to develop an effective defence system to help organisations detect and defend against the peer-to-peer (P2P) botnets. If this research is accomplished successfully, it will be a big step forward in defeating this new but devastating malicious software widely utilised by Internet criminals and terrorists. The capability of a nation to defend against the P2P botnet attacks on its information infrastructure is central to the control of such attacks and hence to a nation's long-term survival and prosperity. The outcomes of this project can be directly used in Australian research communities and adopted by industry and government agencies.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
Discovery Early Career Researcher Award - Grant ID: DE190100046
Funder
Australian Research Council
Funding Amount
$387,000.00
Summary
Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established ....Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established statistical framework utilised in ecology research to provide fundamental insights to boosting the efficiency of software vulnerability discovery, and on the trade-off between investing more resources and gaining better cyber security guarantees. As our reliance on new technologies is ever growing, this project equips Australia to curb cyber crime cost-effectively.Read moreRead less