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Field of Research : Data security and protection
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  • Researchers (27)
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP230100276

    Funder
    Australian Research Council
    Funding Amount
    $415,000.00
    Summary
    Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptiv .... Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptive trust and integrity preserving methods, and reliable distributed data processing mechanisms to mitigate vulnerabilities in real-time IoT-enabled critical surveillance. This should provide significant benefits to Australia's economy, one of which is the enhanced consumer-centric adoption of IoT for sensitive operations.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP230100246

    Funder
    Australian Research Council
    Funding Amount
    $482,610.00
    Summary
    Deep Learning Attacks and Active Defences: A Cybersecurity Perspective. The belief that deep learning technology is imperative for economic development, military control, and strategic competitiveness has accelerated its development across the globe. However, experience has revealed the disappointing fact that deep learning models are vulnerable to a range of security attacks. Hence, a series of methodologies and defence strategies will be devised that make deep learning systems robust to these .... Deep Learning Attacks and Active Defences: A Cybersecurity Perspective. The belief that deep learning technology is imperative for economic development, military control, and strategic competitiveness has accelerated its development across the globe. However, experience has revealed the disappointing fact that deep learning models are vulnerable to a range of security attacks. Hence, a series of methodologies and defence strategies will be devised that make deep learning systems robust to these attacks. The methodologies require analysing attack lifecycles to identify them in their early stages. With this knowledge, active defence methods and forensic strategies can be developed to ensure efficient defences and prevent further attacks. Moreover, the outputs will be generalisable to most deep learning services.
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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

    Linkage Projects - Grant ID: LP220200808

    Funder
    Australian Research Council
    Funding Amount
    $638,775.00
    Summary
    Improved security and privacy for online platforms. Online platforms provide goods and services to people all over the world in a flexible way. Due to COVID-19, the number of online platforms increased significantly. As more and more business activities are conducted in a virtual environment, there is a corresponding increase in major privacy and security challenges. This project aims to work in the online education industry to provide a revolutionary secure environment for both business owners .... Improved security and privacy for online platforms. Online platforms provide goods and services to people all over the world in a flexible way. Due to COVID-19, the number of online platforms increased significantly. As more and more business activities are conducted in a virtual environment, there is a corresponding increase in major privacy and security challenges. This project aims to work in the online education industry to provide a revolutionary secure environment for both business owners and users. This secure online environment will enable privacy and security guarantees that will be first implemented on our Partner Organisation’s education platform. The developed technologies can be easily adapted to most online-service industries and can be commercialised immediately.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP220100453

    Funder
    Australian Research Council
    Funding Amount
    $343,209.00
    Summary
    Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramat .... Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramatically benefit Australian people and government, especially for the Australian ICT industry for commercializing the research outputs.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP240102140

    Funder
    Australian Research Council
    Funding Amount
    $468,294.00
    Summary
    Data Privacy Protection in Wireless Sensor Networks. This project aims to explore a comprehensive solution for the protection of privacy-sensitive data in wireless sensor networks (WSNs) that are vulnerable to hacking. The project expects to use an innovative approach involving multiple data servers to protect sensor data privacy from data collection to data access and analysis. Expected outcomes of this project include new security and privacy models for WSNs in the setting of multiple servers, .... Data Privacy Protection in Wireless Sensor Networks. This project aims to explore a comprehensive solution for the protection of privacy-sensitive data in wireless sensor networks (WSNs) that are vulnerable to hacking. The project expects to use an innovative approach involving multiple data servers to protect sensor data privacy from data collection to data access and analysis. Expected outcomes of this project include new security and privacy models for WSNs in the setting of multiple servers, new secure protocols, privacy-preserving access control and data analysis protocols, and a prototype of a privacy-preserving WSN system. This should provide significant benefits, such as improved security of sensitive data in the healthcare system, military, utilities and telecommunications.
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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: 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

    Discovery Projects - Grant ID: DP240101032

    Funder
    Australian Research Council
    Funding Amount
    $513,374.00
    Summary
    Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods an .... Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods and efficient algorithms that will be able to prevent real-time exfiltration and identify previously undetected exfiltration of sensitive data. This should provide significant benefits to governments, defence networks as well as businesses and health sectors, as it will protect them from sophisticated cyber attacks.
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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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