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Research Topic : computer-assisted morphometry
Socio-Economic Objective : National Security
Australian State/Territory : ACT
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  • Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE170101081

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis t .... Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis to efficiently and precisely analyse large-scale programs according to clients’ needs, thereby allowing compilers to generate safe, reliable and secure code. This project is expected to advance value-flow analysis for industrial-sized software, improve software reliability and security, and benefit Australian software systems and industries.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190103660

    Funder
    Australian Research Council
    Funding Amount
    $385,000.00
    Summary
    Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord .... Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200103207

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor .... Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor authentication performance, which is not commercially applicable. This project aims to investigate innovative solutions to this issue. The intended deliverables will include deep learning based biometric feature extractor, cancellable biometrics and cloud oriented biometrics security protocols.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210102607

    Funder
    Australian Research Council
    Funding Amount
    $523,724.00
    Summary
    Exploiting the Symmetry of Spatial Awareness for 21st Century Automation. This project aims to enable autonomous robotic systems to operate more robustly and more reliably in the complex, cluttered and dynamic environments found in real-world applications. Applying the latest understanding of symmetry in non-linear systems and control provides tools that can be used to develop new design methodologies for spatial awareness algorithms. The outcomes of this project should increase Australia's ca .... Exploiting the Symmetry of Spatial Awareness for 21st Century Automation. This project aims to enable autonomous robotic systems to operate more robustly and more reliably in the complex, cluttered and dynamic environments found in real-world applications. Applying the latest understanding of symmetry in non-linear systems and control provides tools that can be used to develop new design methodologies for spatial awareness algorithms. The outcomes of this project should increase Australia's capacity in high-tech systems and deliver world best open source code for spatial awareness problems to enable the next generation of automation in Australia.
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    Showing 1-4 of 4 Funded Activites

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