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Research Topic : Affective computing
Status : Active
Socio-Economic Objective : Cybersecurity
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  • Active Funded Activity

    ARC Future Fellowships - Grant ID: FT220100046

    Funder
    Australian Research Council
    Funding Amount
    $884,889.00
    Summary
    Provably Secure Cryptography Techniques: Effective, Elegant, and Economic. This project aims to contribute to advanced knowledge and techniques to remove relaxed proof factors from provable security. Cryptography nowadays can be proven secure and must be provably secure before being adopted for data protection. Until today, most cryptography schemes are still using some relaxed proof factors to prove security, but using these relaxed factors was risky. The expected outcomes are proof methodolog .... Provably Secure Cryptography Techniques: Effective, Elegant, and Economic. This project aims to contribute to advanced knowledge and techniques to remove relaxed proof factors from provable security. Cryptography nowadays can be proven secure and must be provably secure before being adopted for data protection. Until today, most cryptography schemes are still using some relaxed proof factors to prove security, but using these relaxed factors was risky. The expected outcomes are proof methodologies for researchers to prove security in an easy way (effective), cryptography techniques for proving security without any relaxed proof factors for cryptography schemes (elegant), and more practical cryptography schemes with elegant proofs to enable Australians to receive benefit from secure data protection (economic).
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    Active Funded Activity

    Linkage Projects - Grant ID: LP230100083

    Funder
    Australian Research Council
    Funding Amount
    $445,009.00
    Summary
    Robust Defences against Adversarial Machine Learning for UAV Systems. This project aims to investigate robust defences for Unmanned Aerial Vehicle (UAV) systems to protect them against adversarial Machine Learning (ML) attacks. This project expects to generate new knowledge in the area of cybersecurity using innovative approaches to safeguard UAV systems from attacks that exploit vulnerabilities in ML models. The expected outcomes of this project include improve techniques for understanding and .... Robust Defences against Adversarial Machine Learning for UAV Systems. This project aims to investigate robust defences for Unmanned Aerial Vehicle (UAV) systems to protect them against adversarial Machine Learning (ML) attacks. This project expects to generate new knowledge in the area of cybersecurity using innovative approaches to safeguard UAV systems from attacks that exploit vulnerabilities in ML models. The expected outcomes of this project include improve techniques for understanding and developing robust ML models and enhanced capacity to design secure UAV systems. This should provide significant benefits, such as improving the security of UAV technology and increasing the reliable use of UAVs for transport and logistics services to support urban and regional communities in Australia.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE230101058

    Funder
    Australian Research Council
    Funding Amount
    $437,254.00
    Summary
    Glass-box Deep Machine Perception for Trustworthy Artificial Intelligence. Explainability and Transparency are the key values for development and deployment of Artificial Intelligence (AI) in Australia’s AI Ethics Framework for industry and governments. This project aims to build new tools to make the central technology of AI - deep learning - transparent and explainable. Its expected outputs are novel theory-driven algorithms and unconventional foundational blocks for deep learning that will al .... Glass-box Deep Machine Perception for Trustworthy Artificial Intelligence. Explainability and Transparency are the key values for development and deployment of Artificial Intelligence (AI) in Australia’s AI Ethics Framework for industry and governments. This project aims to build new tools to make the central technology of AI - deep learning - transparent and explainable. Its expected outputs are novel theory-driven algorithms and unconventional foundational blocks for deep learning that will allow humans to clearly interpret the reasoning process of this technology, which is currently not possible. It is expected to significantly advance our knowledge in machine intelligence and perception. Due to their fundamental nature, the project outcomes are likely to benefit industry and scientific frontiers alike.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE230100001

    Funder
    Australian Research Council
    Funding Amount
    $424,064.00
    Summary
    Regulations in Privacy-Preserving Blockchain Systems. This project aims to develop an integrated regulatory paradigm for privacy-preserving blockchain. This project expects to reduce cybercrimes and illegal transactions in blockchain and provide solutions for the regulation concerns raised in the national blockchain roadmap, using interdisciplinary approaches and new primitives. Expected outcomes of this project include providing versatile regulation services covering the whole lifetime of trans .... Regulations in Privacy-Preserving Blockchain Systems. This project aims to develop an integrated regulatory paradigm for privacy-preserving blockchain. This project expects to reduce cybercrimes and illegal transactions in blockchain and provide solutions for the regulation concerns raised in the national blockchain roadmap, using interdisciplinary approaches and new primitives. Expected outcomes of this project include providing versatile regulation services covering the whole lifetime of transactions while maintaining transaction privacy and user anonymity. This should provide significant benefits to the economy by reducing the financial loss caused by blockchain abuse worldwide ($76 billion per year) and promoting Australia’s blockchain ecosystem (grow to AU$68.4 billion by 2030).
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    Active Funded Activity

    Linkage Projects - Grant ID: LP230100294

    Funder
    Australian Research Council
    Funding Amount
    $394,974.00
    Summary
    High Quality-of-Experience Real-time Video for Smart Online Shopping. This project aims to develop high quality-of-experience real-time video systems for smart shopping applications by devising new deep-neural-network-enhanced video delivery schemes. It will generate new knowledge of combined AI and network solutions to achieve high-quality and low-latency real-time video delivery, addressing unsatisfactory user experience intrinsically caused by network delay and bandwidth. Fundamental principl .... High Quality-of-Experience Real-time Video for Smart Online Shopping. This project aims to develop high quality-of-experience real-time video systems for smart shopping applications by devising new deep-neural-network-enhanced video delivery schemes. It will generate new knowledge of combined AI and network solutions to achieve high-quality and low-latency real-time video delivery, addressing unsatisfactory user experience intrinsically caused by network delay and bandwidth. Fundamental principles and an all-in-one platform will be developed to address research problems and the industrial partner’s practical problems. It will significantly benefit all shopping businesses and their customers in Australia, as well as all other video-related services (e.g., online education, video conferencing, etc.).
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE240100447

    Funder
    Australian Research Council
    Funding Amount
    $438,847.00
    Summary
    The geometry of braids and triangulated categories. Triangulated categories play a central role in geometry, algebra, and topology. Their study can uncover deep structure connecting different areas of mathematics. This project aims to use novel approaches to answer fundamental questions about triangulated categories and their symmetries. These symmetries are encoded by braids, which are important objects with many applications across science. The project is expected to benefit Australia by stimu .... The geometry of braids and triangulated categories. Triangulated categories play a central role in geometry, algebra, and topology. Their study can uncover deep structure connecting different areas of mathematics. This project aims to use novel approaches to answer fundamental questions about triangulated categories and their symmetries. These symmetries are encoded by braids, which are important objects with many applications across science. The project is expected to benefit Australia by stimulating research in mathematics and computer science. It will invite connections with leading experts and students around the world and encourage overseas collaboration. There is a potential long-term benefit to cybersecurity, towards the development of new encryption schemes based on braids.
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    Showing 1-6 of 6 Funded Activites

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