Eat and Dream: effective automatic testing and debugging for real-life embedded wireless communications software. Embedded software is a key enabling technology for the majority of Australian manufacturing industries, including strategically important sectors such as the automotive industry. Embedded wireless communication technologies are playing an increasingly significant role in Australia with a wide range of critical applications ranging from natural disaster early warning to personal healt ....Eat and Dream: effective automatic testing and debugging for real-life embedded wireless communications software. Embedded software is a key enabling technology for the majority of Australian manufacturing industries, including strategically important sectors such as the automotive industry. Embedded wireless communication technologies are playing an increasingly significant role in Australia with a wide range of critical applications ranging from natural disaster early warning to personal health monitoring. Embedded wireless communications software, however, is difficult to test and debug owing to the complexity of the operational environment and complications arising from the interplay between software and hardware. This project will develop an effective and automatic technology to alleviate these difficulties and achieve higher quality software.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
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
Soundness-guided security analysis for android applications. This project aims to develop a soundness-guided programme analysis to mitigate security threats caused by reflection and dynamic class loading in Android apps, without compromising precision and scalability. Both dynamic code update techniques are widely used in benign and malware apps, but state-of-the-art malware analysis tools ignore or mishandle them, missing security threats and vulnerabilities. The resulting open-source security ....Soundness-guided security analysis for android applications. This project aims to develop a soundness-guided programme analysis to mitigate security threats caused by reflection and dynamic class loading in Android apps, without compromising precision and scalability. Both dynamic code update techniques are widely used in benign and malware apps, but state-of-the-art malware analysis tools ignore or mishandle them, missing security threats and vulnerabilities. The resulting open-source security analysis tool will allow software industries and enterprises (from national security, finance, banking to healthcare, retail, telecommunications) to test their mobile software effectively for code defects or security threats early at software development time at significantly reduced cost.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
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
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
A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword ....A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword search, subgraph isomorphism and substructure query techniques. This project is expected to significantly accelerate the application of new technologies, for example, big data analytics and Internet of Things, in many of Australia's critical domains such as e-Health, smart cities, and cybersecurity.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
Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project ....Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project are a family of new context-aware techniques to verify and validate complex behaviours in autonomous driving. This should provide significant benefits, such as safe autonomous driving systems and the improved journey experience and security for road users.Read moreRead less