Secure user authentication with continuous adaptive risk evaluation. Users typically authenticate to any given system only once - when they first access it (for example, through providing a password or fingerprint). The prevalence of single sign-on further allows this single authentication to be sufficient for access to multiple systems. Thus an adversary can obtain a large degree of access from stealing a single password, hijacking a user's session, or even simply borrowing their phone. This pr ....Secure user authentication with continuous adaptive risk evaluation. Users typically authenticate to any given system only once - when they first access it (for example, through providing a password or fingerprint). The prevalence of single sign-on further allows this single authentication to be sufficient for access to multiple systems. Thus an adversary can obtain a large degree of access from stealing a single password, hijacking a user's session, or even simply borrowing their phone. This project aims to develop a continuous authentication approach based on user behaviour - typical interactions plus biometrics (for example, keystroke dynamics) - combined with a risk adaptive assessment of the resources being accessed, resulting in re-authentication requests in the event of a suspected compromise.Read moreRead less
A fast and effective automated insider threat detection and prediction system. Threats from insiders directly compromises the security, privacy and integrity of Australian e-commerce, large databases and communication channels. This project will provide an essential step in combating this criminal activity by developing methods to detect such threats and secure the public's information against exposure and identity theft.
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
Understanding the drivers and motivators of extremist violence. Despite intense interest in the issue, our understanding of and ability to respond to extremist violence is limited. This innovative program of research is designed to establish an empirical foundation for understanding and responding to extremist violence in Australia. It aims to examine risk and protective factors for such violence, the needs of those susceptible to committing such acts, and the effectiveness of intervention. Find ....Understanding the drivers and motivators of extremist violence. Despite intense interest in the issue, our understanding of and ability to respond to extremist violence is limited. This innovative program of research is designed to establish an empirical foundation for understanding and responding to extremist violence in Australia. It aims to examine risk and protective factors for such violence, the needs of those susceptible to committing such acts, and the effectiveness of intervention. Findings are expected to inform health, national security, social welfare, and justice agencies in their pursuit to identify those at risk of offending, address their clinical needs and manage the risk of harm they pose to society and to themselves.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?
Discovery Early Career Researcher Award - Grant ID: DE190100046
Funder
Australian Research Council
Funding Amount
$387,000.00
Summary
Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established ....Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established statistical framework utilised in ecology research to provide fundamental insights to boosting the efficiency of software vulnerability discovery, and on the trade-off between investing more resources and gaining better cyber security guarantees. As our reliance on new technologies is ever growing, this project equips Australia to curb cyber crime cost-effectively.Read moreRead less
Electro-Optical Primers for Safe Use and Clean Manufacturing. Conventional primers contain a mechanically-sensitive primary explosive that is used to detonate the more stable propellant in a bullet. This project aims to address the health and environmental impacts of heavy metals in current primers by replacing them with benign, electrically or optically activated silicon-based materials. Modern semiconductor fabrication techniques will be used to develop safe and clean primers through cost-effe ....Electro-Optical Primers for Safe Use and Clean Manufacturing. Conventional primers contain a mechanically-sensitive primary explosive that is used to detonate the more stable propellant in a bullet. This project aims to address the health and environmental impacts of heavy metals in current primers by replacing them with benign, electrically or optically activated silicon-based materials. Modern semiconductor fabrication techniques will be used to develop safe and clean primers through cost-effective doping and deposition protocols. The expected outcomes of the project include a sovereign primer manufacturing capability for Australia. This will provide a significant strategic advantage and health benefits for law enforcement and defence personnel during live fire training and firing range exercises.Read moreRead less
Foundations for Physically Unclonable nano-Security on Silicon. This project aims to develop an on-chip physical unclonable function (PUF) based on recent progress in nanotechnology to generate unprecedented number of unique signatures. This is significant because these signatures can be used for preventing fraud and counterfeiting, protecting sensitive data and securing communications. PUFs will play an extremely vital role in future security systems. The PUF in the proposed project will be sim ....Foundations for Physically Unclonable nano-Security on Silicon. This project aims to develop an on-chip physical unclonable function (PUF) based on recent progress in nanotechnology to generate unprecedented number of unique signatures. This is significant because these signatures can be used for preventing fraud and counterfeiting, protecting sensitive data and securing communications. PUFs will play an extremely vital role in future security systems. The PUF in the proposed project will be simple, fast, tiny, energy efficient and highly secure as a result of the abundant nano-fabrication variations. The outcome of this project will be a prototype of a super high secure nanoelectronic-based PUF that will be tested to evaluate the technology and its security against malicious attacks.Read moreRead less
Visualisation of latent DNA. This project aims to deliver a proof-of-concept that allows visualisation of invisible DNA (latent DNA) into a quick, inexpensive and practical DNA collection method that will lead to DNA evidence being available in more cases. It will build upon a proof-of-concept method ready for transferal to forensic casework. This will allow DNA evidence recovery technicians to improve their hit rate in recovering latent DNA from real crime items, leading to more informative DNA ....Visualisation of latent DNA. This project aims to deliver a proof-of-concept that allows visualisation of invisible DNA (latent DNA) into a quick, inexpensive and practical DNA collection method that will lead to DNA evidence being available in more cases. It will build upon a proof-of-concept method ready for transferal to forensic casework. This will allow DNA evidence recovery technicians to improve their hit rate in recovering latent DNA from real crime items, leading to more informative DNA profiles. Crime items that currently yield no genetic information will now be informative, assisting investigations of serious crimes or terrorist incidents.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