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Australian State/Territory : WA
Australian State/Territory : ACT
Research Topic : Machine Tools
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  • Active Funded Activity

    Industrial Transformation Training Centres - Grant ID: IC190100031

    Funder
    Australian Research Council
    Funding Amount
    $3,973,202.00
    Summary
    ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understand .... ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understanding and quantifying uncertainty plays in the process. The aim of Data Analytics in Resources and Environment (DARE) is to develop and deliver the data science skills and tools for Australia’s resource industries to make the best possible evidence-based decisions in exploiting and stewarding the nation’s natural resources.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210101348

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an .... Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180100663

    Funder
    Australian Research Council
    Funding Amount
    $450,000.00
    Summary
    Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutt .... Developing A Smart Farming Oriented Secure Data Infrastructure. Smart farming is the future of agriculture. However, recently the Federal Bureau of Investigation has issued a warning that the lack of data privacy and cyber security mechanisms in the field runs a high risk of disaster. This project aims to establish an innovative secure data infrastructure for smart farming including secure and automated smart farming supply-chain management. The deliverables of this project will include the cutting-edge Blockchain based secure IoT data management and privacy-preserving smart contracts for smart farming supply-chain management. This data infrastructure will be the first of its kind which will lay a solid foundation for smart farming technology.
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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: DP190103743

    Funder
    Australian Research Council
    Funding Amount
    $660,000.00
    Summary
    Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical .... Provable elimination of information leakage through timing channels. This project aims to develop techniques to solve the issue in information security of unauthorised information flow resulting from competition for shared hardware resources. The project will combine operating systems design, formal hardware models, information-flow reasoning and theorem proving to achieve a goal that is widely considered infeasible. The project is expected to result in a system that prevents leakage of critical information, such as encryption keys, through timing channels. This should prevent sophisticated attacks on public clouds, mobile devices and military-grade cross-domain devices.
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