Designing Distributed Intrusion Detection Systems for Critical Industrial Infrastructures. SCADA systems are computerized systems that control and monitor industrial and critical infrastructures, such as power grid, gas and water facilities and nuclear power plants. Many cyber-attacks on SCADA systems make such systems vulnerable. Also there is an increasing risk that SCADA vulnerabilities could be exploited by terrorist organizations. The security of SCADA systems of critical infrastructures ha ....Designing Distributed Intrusion Detection Systems for Critical Industrial Infrastructures. SCADA systems are computerized systems that control and monitor industrial and critical infrastructures, such as power grid, gas and water facilities and nuclear power plants. Many cyber-attacks on SCADA systems make such systems vulnerable. Also there is an increasing risk that SCADA vulnerabilities could be exploited by terrorist organizations. The security of SCADA systems of critical infrastructures has enormous and direct impact to our national security, economy and social life because of potential disasters that could happen from natural causes as well as malicious attacks. This project aims to investigate the relevant issues and provide efficient and reliable technological solutions to detect and prevent such problems.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. 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?
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.
Developing smart embedded host-based intrusion detection systems. Computer intrusion is a major concern in many places. It is estimated that cybercrime cost firms US$1 trillion globally in 2008. Many serious cyber attacks, including cyber espionage, do not generate significant network traffic and can easily penetrate network-based intrusion detection systems (NIDS). Such attacks often attempt to compromise individual hosts and hence they are best detected at the host level. We aim to design i ....Developing smart embedded host-based intrusion detection systems. Computer intrusion is a major concern in many places. It is estimated that cybercrime cost firms US$1 trillion globally in 2008. Many serious cyber attacks, including cyber espionage, do not generate significant network traffic and can easily penetrate network-based intrusion detection systems (NIDS). Such attacks often attempt to compromise individual hosts and hence they are best detected at the host level. We aim to design innovative host-based IDS, as a complement to the NIDS, to address this issue. The outcomes of this project will strengthen the national capability to resist attacks by criminals and terrorists on Australian networked critical infrastructures and also enhance the global competitiveness of Australia’s information technology industry.Read moreRead less
Detecting Supervisory Control and Data Access (SCADA) malicious programs to protect Australian critical infrastructure. The security of SCADA systems has enormous impact to our national security and economy because they control and monitor critical infrastructure, like power, gas and water facilities and nuclear power plants, etc. This project aims to investigate the security issues and provide innovative technological solutions to detect and prevent such problems.
Enhancing privacy preserving in dynamic cyberspace. This project aims to develop a novel infrastructure operational monitoring and management strategy to reduce the redundant maintenance actions and achieve a cost-effective approach for civil infrastructure asset management. The project will use multiple social networks as a platform for the project, with the potential for the results to be extended to any dynamic cyberspace. Project outcomes will include a set of new analysis theories and tools ....Enhancing privacy preserving in dynamic cyberspace. This project aims to develop a novel infrastructure operational monitoring and management strategy to reduce the redundant maintenance actions and achieve a cost-effective approach for civil infrastructure asset management. The project will use multiple social networks as a platform for the project, with the potential for the results to be extended to any dynamic cyberspace. Project outcomes will include a set of new analysis theories and tools to facilitate government, companies, individuals, and organisations to enhance their information gathering and privacy-preserving capabilities. This is expected to enhance the credibility of the government and organisations and save the possible financial loss of companies and individuals.Read moreRead less
Privacy preservation for personalised smart devices. The goal of this project is to build a privacy preservation framework for personalised smart devices with both immediate and long-term applications in a range of industries. The novel theoretical contributions include a privacy-preservation mechanism that guards against attacks by intelligent tools, a model and metrics that distinguish between object detection and object recognition, and allowing users to specify their desired level of privacy ....Privacy preservation for personalised smart devices. The goal of this project is to build a privacy preservation framework for personalised smart devices with both immediate and long-term applications in a range of industries. The novel theoretical contributions include a privacy-preservation mechanism that guards against attacks by intelligent tools, a model and metrics that distinguish between object detection and object recognition, and allowing users to specify their desired level of privacy guarantee. Practically, these solutions have clear economic and public-safety benefits. The solutions will accelerate AI device development, advance smart technologies based on individual behaviours, and guarantee personal data privacy against both human attackers and adversarial algorithms. Read moreRead less
Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges ....Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges and expects to establish innovative research and solutions for enabling full lifecycle privacy protection on cloud. The project outcomes will help to safeguard Australian community in fast-growing online cyber world, and benefit to fast-growing privacy sensitive data hosting and applications on cloud.Read moreRead less
Blockchain-Enabled Federated Learning for Secure and Decentralised Learning. This project aims to develop novel blockchain-enabled federated learning techniques for secure and decentralised learning. It addresses an important and urgent machine learning problem, that is, the data useful for training machine learning models are often held by different owners who are not willing to share their data due to privacy concerns, resulting in isolated data islands. The project will result in a set of inn ....Blockchain-Enabled Federated Learning for Secure and Decentralised Learning. This project aims to develop novel blockchain-enabled federated learning techniques for secure and decentralised learning. It addresses an important and urgent machine learning problem, that is, the data useful for training machine learning models are often held by different owners who are not willing to share their data due to privacy concerns, resulting in isolated data islands. The project will result in a set of innovative algorithms that provide solutions to the key challenges in blockchain-enabled federated learning. The expected outcomes of the project will dramatically advance the frontier of machine learning and blockchain research, and have massive social and economic benefits for Australia and international communities.Read moreRead less