A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driv ....A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driving models. The project will lead to two innovations: in theory design an attack detection and prevention ecosystem for autonomous driving and in application implement a safety analysis toolset for industry-scale autonomous systems.Read moreRead less
Cost-effective App Service Management in Edge Computing Environment. This project aims to deliver a framework and a suite of approaches for cost-effective app service management in the edge computing (EC) environment facilitated by the 5G mobile network. Edge computing offers great promises for rapidly advancing mobile and IoT apps in many active domains in Australia, e.g., self-driving cars, medical services, etc. Using a variety of optimization techniques and game theory, this project attacks ....Cost-effective App Service Management in Edge Computing Environment. This project aims to deliver a framework and a suite of approaches for cost-effective app service management in the edge computing (EC) environment facilitated by the 5G mobile network. Edge computing offers great promises for rapidly advancing mobile and IoT apps in many active domains in Australia, e.g., self-driving cars, medical services, etc. Using a variety of optimization techniques and game theory, this project attacks the new challenges in the deployment, delivery and adaptation of app services in the EC environment. The outcomes of this project will significantly promote new mobile and IoT apps over Australia's 5G mobile network by allowing app vendors to manage their services cost-effectively with ease in the EC environment.Read moreRead less
Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a unive ....Effective software vulnerability detection for web services. This project aims to design and implement new and better methods to find vulnerabilities in software services delivered over the web or through the cloud, as well as methods for proving the absence of certain types of vulnerability. So-called injection attacks are pervasive and generally considered the most important security threat on today's Internet. The programming languages used for software services tend to use strings as a universal data structure, which unfortunately makes it hard to separate trusted code from untrusted user-provided data. This project intends to develop novel program analysis tools and string constraint solvers, and employ these tools to support sophisticated automated reasoning about string manipulating software.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
Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not o ....Scalable & Accountable Privacy-Preserving Blockchain with Enhanced Security. This project aims to address the scalability and accountability of privacy-preserving blockchain by advancing cryptographic techniques. This project expects to develop scalable protocols for privacy-preserving blockchain while also adding accountability for authority to trace cyber crime activities, which is a missing piece in any state-of-the-art public blockchain system. Expected outcomes of this project include not only practical solutions for protecting sensitive data recorded in blockchain but also crucial techniques to make the blockchain accountable for practical applications with enhanced security. This project provides significant benefits, such as building a trusted environment for sensitive transactions in the digital economy.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
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
Development of Cryptographic Library and Support System. The protection of the whole cyber space relies on a foundation of cryptography. Cryptographic components of apps authenticate remote parties and secure the communications. However, cryptographic misuse has become a most common issue in development of security component, affecting up to 90% of apps!
This project aims to research, design and develop a crypto library. The innovation of this project lays in three aspects: (1) we will develop ....Development of Cryptographic Library and Support System. The protection of the whole cyber space relies on a foundation of cryptography. Cryptographic components of apps authenticate remote parties and secure the communications. However, cryptographic misuse has become a most common issue in development of security component, affecting up to 90% of apps!
This project aims to research, design and develop a crypto library. The innovation of this project lays in three aspects: (1) we will develop a self-contained, reliable, compatible and verifiable crypto library; (2) we will develop security test software automatically to test and verify security of codes; and (3) we will provide intelligent decision support through argumentation to help developers to apply the library efficiently and correctly.Read moreRead less
Developing an active defence system to identify malicious domains and websites. This project aims to develop an innovative active defence system to effectively identify malicious Internet domains and websites. It can secure the cyberspace that is essential to the daily work of Australian people, thus addresses a fundamental problem in safeguarding Australia from cyber crime and terrorism.
Discovery Early Career Researcher Award - Grant ID: DE170100641
Funder
Australian Research Council
Funding Amount
$305,754.00
Summary
Priced attribute-based encryption and its applications. This project aims to develop Priced Attribute-Based Encryption (PABE), a security mechanism. Access control is important for secure online information access. Access to encrypted data requires both private key and payment from earmarked funds specified by the access policy of encrypted data. This research will enable both authorisation and restriction of users while they access protected data anonymously. Expected outcomes include new model ....Priced attribute-based encryption and its applications. This project aims to develop Priced Attribute-Based Encryption (PABE), a security mechanism. Access control is important for secure online information access. Access to encrypted data requires both private key and payment from earmarked funds specified by the access policy of encrypted data. This research will enable both authorisation and restriction of users while they access protected data anonymously. Expected outcomes include new models, theories, techniques and PABE constructions. This research project is expected to contribute to cyber security in anonymous access control with advanced management for all Australians.Read moreRead less