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
Reputation-based trust management in crowdsourcing environments. This project aims to address the critical need for enabling trustworthy crowd sourcing environments. Expected outcomes include innovative solutions to evaluate the reputation and expertise portfolio of workers and identify malicious workers, with the ultimate goal of making personalised recommendations of trustworthy workers with expertise to the requesters who have published tasks. This project is expected to provide key solutions ....Reputation-based trust management in crowdsourcing environments. This project aims to address the critical need for enabling trustworthy crowd sourcing environments. Expected outcomes include innovative solutions to evaluate the reputation and expertise portfolio of workers and identify malicious workers, with the ultimate goal of making personalised recommendations of trustworthy workers with expertise to the requesters who have published tasks. This project is expected to provide key solutions to globally leading crowd sourcing platforms originating in Australia and benefit Australian and worldwide Internet users.Read moreRead less
Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applicatio ....Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applications of significant social, environmental and economic value, such as Location-Aware Service, Environment Monitoring, Augmented Reality, Autonomous Vehicle, and Rapid Emergency Response. The project will enhance Australia's international competitive advantage in forefront of ICT research and technology innovation.Read moreRead less
Techniques for active conceptual modelling and guided data mining for rapid knowledge discovery. Quick, accurate responses to rapidly evolving phenomena are essential. This project will develop a platform able to accept data from a variety of sources in advance of the full definition of the associated conceptual model. The project will facilitate rapid querying and direct manipulation of the mining process allowing fast, user-oriented results.
Discovery Early Career Researcher Award - Grant ID: DE140100215
Funder
Australian Research Council
Funding Amount
$394,752.00
Summary
Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genui ....Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genuine preferences from travel histories, due to lack of consideration for activity information as well as the associated semantics and context. This project aims to address these issues and provide effective recommendations by considering both users’ intention and collective behavioural knowledge inferred from activity trajectories.Read moreRead less
Active Management of Complex Non-self-finalising Behaviours through Deep Analytics. This project aims to build theoretical breakthroughs and novel tools for deep analytics and active management of non-self-finalising (NSF) individual and business behaviours, which are sophisticated and increasingly seen in public sectors such as taxation and business including banking and insurance. The challenging economic environment continues to make managing NSF behaviours difficult. To date, there are no su ....Active Management of Complex Non-self-finalising Behaviours through Deep Analytics. This project aims to build theoretical breakthroughs and novel tools for deep analytics and active management of non-self-finalising (NSF) individual and business behaviours, which are sophisticated and increasingly seen in public sectors such as taxation and business including banking and insurance. The challenging economic environment continues to make managing NSF behaviours difficult. To date, there are no sufficient theories or effective systems in data mining and behavioural science to systematically learn the intent, impact and patterns of NSF behaviours, and to suggest cost-effective responses to these behaviours. This project aims to ensure Australia’s leading role in innovation for evidence-driven enterprise behaviour analytics and management.Read moreRead less
Detecting significant changes in organisation-customer interactions leading to non-compliance. The instant detection of risky customer and/or group dynamics and business policy and/or process changes dispersed in normal interactions can avoid immense losses and inconsistent policies for Government and industries, such as preventing Centrelink customer debt. This project will deliver novel analytical techniques and smart information use to effectively detect the above-mentioned changes leading to ....Detecting significant changes in organisation-customer interactions leading to non-compliance. The instant detection of risky customer and/or group dynamics and business policy and/or process changes dispersed in normal interactions can avoid immense losses and inconsistent policies for Government and industries, such as preventing Centrelink customer debt. This project will deliver novel analytical techniques and smart information use to effectively detect the above-mentioned changes leading to non-compliance. It will enhance service quality, compliance, payment accuracy and policy design for the Australian Government and industries such as Centrelink, the Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA), banking and insurance. The resulting systems, the researchers trained and resulting publications will significantly enhance Australia's leading role in tackling change-driven non-compliance.Read moreRead less
Modelling and discovering complex interaction relations hidden in group behaviours in businesses, online and social communities. This project addresses the shortage in current behavior analysis by inventing innovative theories and algorithms for analysing complex relations and interactions in group behaviours. The outcomes of this project will enable effective detection of suspicious large groups, contributing to safer businesses and society and improved compliance in online and social communiti ....Modelling and discovering complex interaction relations hidden in group behaviours in businesses, online and social communities. This project addresses the shortage in current behavior analysis by inventing innovative theories and algorithms for analysing complex relations and interactions in group behaviours. The outcomes of this project will enable effective detection of suspicious large groups, contributing to safer businesses and society and improved compliance in online and social communities.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL170100117
Funder
Australian Research Council
Funding Amount
$3,208,192.00
Summary
On snapping up semantics of dynamic pixels from moving cameras. The project aims to develop a suite of original models and algorithms for processing and understanding videos captured by moving cameras, and to establish the mathematical foundations for deep learning-based computer vision to provide theoretical underpinnings. The project expects to generate new knowledge that will transform moving-camera computer vision with step-changes in visual quality enhancement, compression and acceleration ....On snapping up semantics of dynamic pixels from moving cameras. The project aims to develop a suite of original models and algorithms for processing and understanding videos captured by moving cameras, and to establish the mathematical foundations for deep learning-based computer vision to provide theoretical underpinnings. The project expects to generate new knowledge that will transform moving-camera computer vision with step-changes in visual quality enhancement, compression and acceleration technologies, and solutions for fundamental computer vision tasks. A new concept of feature complexity for measuring the discriminant and learnable abilities of features from deep models will also be defined. The outcomes of the project will be critical for enabling autonomous machines to perceive and interact with the environment.Read moreRead less
Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and w ....Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and will create new knowledge to harness the full potential of crowd sourced data curation. This is expected to make a significant benefit towards enhanced organisational capacity to accelerate the time-to-value from data analytics projects.Read moreRead less