Towards a block-cipher circuit resistant to multiple side channel attacks. This project aims to design, implement and verify the first ever fully comprehensive countermeasure against simultaneous attacks on devices performing a cryptographic task, such as a smart card or a mobile phone used for an electronic payment, through a variety of side channels. Side channel attacks aim to obtain unauthorized access to secret cryptographic keys used by such devices, by collecting and statistically process ....Towards a block-cipher circuit resistant to multiple side channel attacks. This project aims to design, implement and verify the first ever fully comprehensive countermeasure against simultaneous attacks on devices performing a cryptographic task, such as a smart card or a mobile phone used for an electronic payment, through a variety of side channels. Side channel attacks aim to obtain unauthorized access to secret cryptographic keys used by such devices, by collecting and statistically processing measurements of by-products of the physical operation of these devices, such as the consumed power or electromagnetic radiation. Rapid proliferation of personal devices used for electronic payments or containing sensitive data makes such a comprehensive countermeasure urgently needed.Read moreRead less
Design automation for secure, reliable and energy efficient embedded processors. This project seeks to create a methodology to design and generate processors which are both secure, reliable and energy efficient for deployment in Internet of Things (IoT) systems, which require little on-going maintenance. In such systems, both security and reliability are paramount, particularly in medical devices, control devices in critical machinery, financial transactions and automotive electronics. The proje ....Design automation for secure, reliable and energy efficient embedded processors. This project seeks to create a methodology to design and generate processors which are both secure, reliable and energy efficient for deployment in Internet of Things (IoT) systems, which require little on-going maintenance. In such systems, both security and reliability are paramount, particularly in medical devices, control devices in critical machinery, financial transactions and automotive electronics. The project will use an open RISC-V processor which is sufficiently flexible to function as a base processor, with a myriad of tools such as compilers and debuggers available. Reliable computing machinery will enable systems to work in hostile environments and be functionally correct for longer.Read moreRead less
Privacy-aware Smart Access Control for Internet-of-Things on Blockchain. This project aims to address privacy and trust issues in Internet-of-Things (IoT) access control mechanism of smart critical infrastructure. This project expects to generate new knowledge in the area of IoT access control by leveraging privacy-preserving techniques, blockchain, and machine learning. Expected outcomes of this project include enhanced capability to build improved techniques for privacy aware tamperproof IoT a ....Privacy-aware Smart Access Control for Internet-of-Things on Blockchain. This project aims to address privacy and trust issues in Internet-of-Things (IoT) access control mechanism of smart critical infrastructure. This project expects to generate new knowledge in the area of IoT access control by leveraging privacy-preserving techniques, blockchain, and machine learning. Expected outcomes of this project include enhanced capability to build improved techniques for privacy aware tamperproof IoT access control with machine learning based anomaly detection. This should provide significant benefits, such as preventing cyber threats on security and privacy of IoT and improving trust in IoT-enabled smart critical infrastructure of Australia.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100680
Funder
Australian Research Council
Funding Amount
$403,482.00
Summary
Making Anomaly Detection Interpretable & Actionable in Hostile Environments. Anomaly detection plays a vital role in cyber security to identify threat patterns hidden within large volumes of data. However, current approaches experience high false alarm rates in noisy, heterogeneous and adversarial environments. This project aims to identify and interpret anomalies that can disrupt system performance by introducing the concept of actionable anomalies. It will significantly advance the effectivene ....Making Anomaly Detection Interpretable & Actionable in Hostile Environments. Anomaly detection plays a vital role in cyber security to identify threat patterns hidden within large volumes of data. However, current approaches experience high false alarm rates in noisy, heterogeneous and adversarial environments. This project aims to identify and interpret anomalies that can disrupt system performance by introducing the concept of actionable anomalies. It will significantly advance the effectiveness of anomaly detection by developing algorithms that distil local and global structures of data to characterise actionable anomalies and explain their outlying aspects. Project outcomes will enhance the security, trustworthiness and fault-tolerance of critical systems, contributing to international efforts in cyber security.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100584
Funder
Australian Research Council
Funding Amount
$370,000.00
Summary
Secure and Private Machine Learning. This project intends to answer the question: How can machines learn from data when participants behave maliciously for personal gain? Machine learning and statistics are used in many technologies where participants have an incentive to game the system (eg internet ad placement, e-commerce rating systems, credit risk in finance, health analytics and smart utility grids). However, little is known about how well state-of-the-art statistical inference techniques ....Secure and Private Machine Learning. This project intends to answer the question: How can machines learn from data when participants behave maliciously for personal gain? Machine learning and statistics are used in many technologies where participants have an incentive to game the system (eg internet ad placement, e-commerce rating systems, credit risk in finance, health analytics and smart utility grids). However, little is known about how well state-of-the-art statistical inference techniques fare when data is manipulated by a malicious participant. The project's outcomes aim to ensure that statistical analysis is accurate while preserving data privacy, providing theoretical foundations of secure machine learning in adversarial domains. Potential applications range from cybersecurity defences to measures for balancing security and privacy interests.Read moreRead less
Intruder alert! detecting and classifying events in noisy time series. This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enabl ....Intruder alert! detecting and classifying events in noisy time series. This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time series generated from perimeter security systems. The project expects to develop robust methods to detect intrusion events under different operating environments while ignoring nuisance events. The project will boost the global competitiveness of the Australian security industry, and enable improved event detection and classification in noisy time series to the benefit of many critical application areas beyond national security.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170101203
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Multi-functional antenna arrays for secure and reliable wireless systems. This project aims to develop and validate the fundamental theory and engineering techniques for fully reconfigurable antenna arrays. Multi-functional antennae deliver highly-secure and reliable wireless communications for Australia’s digital economy. Such an antenna array, a critical component of wireless multi-functional systems, can provide full flexibilities of the frequency, polarisation and radiation pattern to satisf ....Multi-functional antenna arrays for secure and reliable wireless systems. This project aims to develop and validate the fundamental theory and engineering techniques for fully reconfigurable antenna arrays. Multi-functional antennae deliver highly-secure and reliable wireless communications for Australia’s digital economy. Such an antenna array, a critical component of wireless multi-functional systems, can provide full flexibilities of the frequency, polarisation and radiation pattern to satisfy the systems’ different requirements. This project is expected to advance the scientific knowledge of several frontiers of antenna research and enhance spectrum usage efficiency, highly-secure wireless communications and compact and reliable military wireless platforms, thus benefiting Australian industry, society and national defence.Read moreRead less
Machine learning in adversarial environments. Machine learning underpins the technologies driving the economies of both Silicon Valley and Wall Street, from web search and ad placement, to stock predictions and efforts in fighting cybercrime. This project aims to answer the question: How can machines learn from data when contributors act maliciously for personal gain?
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.Read moreRead less
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. Read moreRead less