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Scheme : Linkage Projects
Field of Research : Cryptography
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP220100332

    Funder
    Australian Research Council
    Funding Amount
    $391,412.00
    Summary
    Cryptographic Group Actions and Their Applications. This project aims to develop innovative techniques to construct cryptographic primitives and explore their applications to secure cloud computing. Cryptographic group actions have recently become a promising candidate for post-quantum cryptography. However, whilst possessing strong mathematical complexity, group actions are still in their infancy, and thus it remains challenging to realise advanced cryptographic constructions. The expected outc .... Cryptographic Group Actions and Their Applications. This project aims to develop innovative techniques to construct cryptographic primitives and explore their applications to secure cloud computing. Cryptographic group actions have recently become a promising candidate for post-quantum cryptography. However, whilst possessing strong mathematical complexity, group actions are still in their infancy, and thus it remains challenging to realise advanced cryptographic constructions. The expected outcomes of this project are new techniques from cryptographic group actions and their applications to secure cloud services. This will provide direct benefits to Australia's Industry 4.0 adoption by enabling advanced technologies developed in Australia in the upcoming era of quantum computers.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP220200649

    Funder
    Australian Research Council
    Funding Amount
    $330,204.00
    Summary
    Privacy-Preserving Collaborative Analytics on Sensitive Data. This project aims to develop efficient solutions that allow multiple institutes to carry out collaborative analytics on aggregated data without revealing their sensitive data to each other. The project expects to remedy acute privacy concerns when institutes share sensitive data across boundaries for collective insights. The expected outcomes include a hybrid trust model with distributed trusts to provide malicious security guarantees .... Privacy-Preserving Collaborative Analytics on Sensitive Data. This project aims to develop efficient solutions that allow multiple institutes to carry out collaborative analytics on aggregated data without revealing their sensitive data to each other. The project expects to remedy acute privacy concerns when institutes share sensitive data across boundaries for collective insights. The expected outcomes include a hybrid trust model with distributed trusts to provide malicious security guarantees, lightweight privacy-enhancing techniques to express rich analytical functionalities, and a system platform for real-world applications. This should provide significant benefits such as facilitating industries to safeguard their customers' data and uplift their businesses in a secure and trustworthy fashion.
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