Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise deve ....Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise developed from the project will provide a competitive edge for Australian industries in aerospace, oceanography, robotics, remote sensing, and biomedical engineering. Read moreRead less
Robust next-generation detection techniques to defend operational networks against attacks. As networks are fast becoming one of the pillars of our society, network security is essential.
Without good security, networks will be unreliable, more costly, and restricted in the capabilities they can offer. The project will allow advanced anomaly and intrusion detection techniques to be used in the ultra-high speeds of the Internet core. It will provide the groundwork for the attack detection and p ....Robust next-generation detection techniques to defend operational networks against attacks. As networks are fast becoming one of the pillars of our society, network security is essential.
Without good security, networks will be unreliable, more costly, and restricted in the capabilities they can offer. The project will allow advanced anomaly and intrusion detection techniques to be used in the ultra-high speeds of the Internet core. It will provide the groundwork for the attack detection and prevention infrastructure of the future. 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?