Novel audio watermarking techniques for tracing multimedia piracy. This project aims to develop inaudible, high-capacity audio watermarking techniques to trace the illegal copying and distribution of multimedia data containing a sound component, such as audios and sound videos. With the rapid growth of communication networks and the use of advanced multimedia technology, digital multimedia data can be easily copied, manipulated and distributed. This has led to strong demand for new techniques to ....Novel audio watermarking techniques for tracing multimedia piracy. This project aims to develop inaudible, high-capacity audio watermarking techniques to trace the illegal copying and distribution of multimedia data containing a sound component, such as audios and sound videos. With the rapid growth of communication networks and the use of advanced multimedia technology, digital multimedia data can be easily copied, manipulated and distributed. This has led to strong demand for new techniques to prevent illegal use of copyrighted data. The project is expected to advance the theory of audio watermarking and enhance Australia's international competitiveness in this field.
Read moreRead less
A provable privacy-preserving data sharing system for the cloud environment. This project aims to develop an innovative data sharing system, with a mathematically provable privacy guarantee, in a cloud environment. This will be adopted by Australian Education Management Group’s (AEMG) cloud campus to exchange data in a restricted privacy manner between partner institutions. It will be commercialised as a middleware that can be plugged into existing cloud environments to maintain required privacy ....A provable privacy-preserving data sharing system for the cloud environment. This project aims to develop an innovative data sharing system, with a mathematically provable privacy guarantee, in a cloud environment. This will be adopted by Australian Education Management Group’s (AEMG) cloud campus to exchange data in a restricted privacy manner between partner institutions. It will be commercialised as a middleware that can be plugged into existing cloud environments to maintain required privacy even when the cloud crosses various jurisdictions with different privacy policies. The outcomes will benefit educational organisations, and lay the foundations for data sharing in other communities such as the government, banks, and other industries in Australia.Read moreRead less
Developing an active defence system to identify malicious domains and websites. This project aims to develop an innovative active defence system to effectively identify malicious Internet domains and websites. It can secure the cyberspace that is essential to the daily work of Australian people, thus addresses a fundamental problem in safeguarding Australia from cyber crime and terrorism.
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
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
An active approach to detect and defend against peer-to-peer botnets. The aim of this project is to develop an effective defence system to help organisations detect and defend against the peer-to-peer (P2P) botnets. If this research is accomplished successfully, it will be a big step forward in defeating this new but devastating malicious software widely utilised by Internet criminals and terrorists. The capability of a nation to defend against the P2P botnet attacks on its information infrastru ....An active approach to detect and defend against peer-to-peer botnets. The aim of this project is to develop an effective defence system to help organisations detect and defend against the peer-to-peer (P2P) botnets. If this research is accomplished successfully, it will be a big step forward in defeating this new but devastating malicious software widely utilised by Internet criminals and terrorists. The capability of a nation to defend against the P2P botnet attacks on its information infrastructure is central to the control of such attacks and hence to a nation's long-term survival and prosperity. The outcomes of this project can be directly used in Australian research communities and adopted by industry and government agencies.Read moreRead less
New Efficient Cryptographic Tools for Data Privacy and Software Protection. Online services for collaborative communication and software distribution are commonplace today, but their use is hampered by data privacy breaches and intellectual property violations via software reverse engineering. Recent theoretical breakthroughs in cryptography promise to provide new powerful tools for solving these problems, but these tools are not yet suitable for practical use, due to their low efficiency and a ....New Efficient Cryptographic Tools for Data Privacy and Software Protection. Online services for collaborative communication and software distribution are commonplace today, but their use is hampered by data privacy breaches and intellectual property violations via software reverse engineering. Recent theoretical breakthroughs in cryptography promise to provide new powerful tools for solving these problems, but these tools are not yet suitable for practical use, due to their low efficiency and a lack of solid security foundations. This project aims to apply algebraic and probabilistic techniques to improve efficiency of existing tools, and the understanding of their security. Outcomes are expected to include new insights in cryptographic theory, and new practical tools for cyber security.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.
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
Privacy-Preserving Classification for Big-Data Driven Network Traffic. Protecting sensitive information in large network traffic flows while ensuring data usability for classification emerges as a critical problem of increasing significance. Existing techniques do not work on highly heterogeneous traffic from big-data applications for both privacy protection and classification (such as port-based and load- based methods). This project investigates new theories, methods and techniques for solving ....Privacy-Preserving Classification for Big-Data Driven Network Traffic. Protecting sensitive information in large network traffic flows while ensuring data usability for classification emerges as a critical problem of increasing significance. Existing techniques do not work on highly heterogeneous traffic from big-data applications for both privacy protection and classification (such as port-based and load- based methods). This project investigates new theories, methods and techniques for solving this problem. It proposes to develop a set of effective methods for privacy-preserving data publication through combining randomisation with anonymisation, and for classifying the published data through uncertainty leveraging by probabilistic reasoning and accuracy lifting by inter-flow correlation analysis and active learning.Read moreRead less