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Research Topic : missing data
Australian State/Territory : WA
Scheme : Discovery Projects
Australian State/Territory : ACT
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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

    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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    Funded Activity

    Discovery Projects - Grant ID: DP140100522

    Funder
    Australian Research Council
    Funding Amount
    $385,000.00
    Summary
    Signal Processing for Reconfigurable Antennas – a Multidisciplinary Approach for Next Generation Wireless Communications. To satisfy the enormous demand for wireless applications with scarce radio spectrum, new technologies must be researched, developed, and then employed. Reconfigurable antennas, through morphing their physical structures with various switches, can adapt to the radio propagation environment, thereby increasing spectrum efficiency and power efficiency of wireless communications. .... Signal Processing for Reconfigurable Antennas – a Multidisciplinary Approach for Next Generation Wireless Communications. To satisfy the enormous demand for wireless applications with scarce radio spectrum, new technologies must be researched, developed, and then employed. Reconfigurable antennas, through morphing their physical structures with various switches, can adapt to the radio propagation environment, thereby increasing spectrum efficiency and power efficiency of wireless communications. This project aims to design signal processing algorithms for achieving all the benefits that reconfigurable antennas can provide for wireless communications. An important outcome of this research is sound channel models validated by extensive field measurement data.
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    Showing 1-4 of 4 Funded Activites

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