Development of Cryptographic Library and Support System. The protection of the whole cyber space relies on a foundation of cryptography. Cryptographic components of apps authenticate remote parties and secure the communications. However, cryptographic misuse has become a most common issue in development of security component, affecting up to 90% of apps!
This project aims to research, design and develop a crypto library. The innovation of this project lays in three aspects: (1) we will develop ....Development of Cryptographic Library and Support System. The protection of the whole cyber space relies on a foundation of cryptography. Cryptographic components of apps authenticate remote parties and secure the communications. However, cryptographic misuse has become a most common issue in development of security component, affecting up to 90% of apps!
This project aims to research, design and develop a crypto library. The innovation of this project lays in three aspects: (1) we will develop a self-contained, reliable, compatible and verifiable crypto library; (2) we will develop security test software automatically to test and verify security of codes; and (3) we will provide intelligent decision support through argumentation to help developers to apply the library efficiently and correctly.Read moreRead less
Learning complex classifiers without search. This project investigates novel approaches to computational data analysis that use new forms of probabilistic models of data. These new approaches complement the state-of-the-art, suiting large quantities of categorical data, being robust in the presence of errors, and efficiently handling updates when new data become available.
Decentralised Data Management for Edge Caching Systems in 5G. This project aims to deliver a suite of decentralised data management approaches to facilitate practical edge caching systems in the 5G mobile edge computing (MEC) environment. Edge caching offers great promises for Australia's post-COVID economic recovery and resilience with the ability to enable real-time mobile and IoT software applications in various domains, e.g., telehealth, online learning/working, advanced manufacturing, etc. ....Decentralised Data Management for Edge Caching Systems in 5G. This project aims to deliver a suite of decentralised data management approaches to facilitate practical edge caching systems in the 5G mobile edge computing (MEC) environment. Edge caching offers great promises for Australia's post-COVID economic recovery and resilience with the ability to enable real-time mobile and IoT software applications in various domains, e.g., telehealth, online learning/working, advanced manufacturing, etc. This project tackles new and urgent challenges in edge data storage, manipulation, maintenance, and protection with optimisation, distributed consensus, graph analytics, and cryptography techniques. The outcomes should build the pillars of edge caching systems and promote Australia's 5G software innovations.Read moreRead less
Efficient and effective algorithms for searching strings in secondary storage. Pattern searching is fundamental to a wide range of computing applications, including web search and bioinformatics. In this project we will develop compression algorithms and hybrid memory-disk search structures that allow fast pattern matching on sequences of textual and numeric data, including when approximate search is required.
Automatic video annotation by learning from web data. This project aims to study next-generation video annotation technologies to automatically tag raw videos using a huge set of semantic concepts. The project will study new domain adaptation schemes and frameworks in order to substantially improve video annotation performance. The resulting prototype system can be directly used by ordinary users worldwide to search their personal videos using textual queries. The system is also applicable to vi ....Automatic video annotation by learning from web data. This project aims to study next-generation video annotation technologies to automatically tag raw videos using a huge set of semantic concepts. The project will study new domain adaptation schemes and frameworks in order to substantially improve video annotation performance. The resulting prototype system can be directly used by ordinary users worldwide to search their personal videos using textual queries. The system is also applicable to video surveillance applications, which can enhance Australia’s homeland security.Read moreRead less
Big Data Machines: Internet-Scale Machine Learning Techniques to Combat the Curse of Big Data. The advent of “big data” in business, government, science, social networks, the internet, etc. creates opportunity in business and commercial domains. Big data also raises issues of increasing volume, variety, dimensionality and categories in open domain big data applications, which this project will solve by developing novel machine learning techniques, including theoretical foundations, a big data ma ....Big Data Machines: Internet-Scale Machine Learning Techniques to Combat the Curse of Big Data. The advent of “big data” in business, government, science, social networks, the internet, etc. creates opportunity in business and commercial domains. Big data also raises issues of increasing volume, variety, dimensionality and categories in open domain big data applications, which this project will solve by developing novel machine learning techniques, including theoretical foundations, a big data machine learning framework and open source website. The outcomes of this project will provide frontier technologies for big data analysis that will have social and economic impact in such areas as social media computing, bioinformatics and business intelligence, and enhance Australia’s global position in the pattern recognition and data mining communities.Read moreRead less
Learning Specific Ontology for Un-Supervised Text Classification. The dramatic rise in massive text data has led to an increasing number of challenges in scalability and noisy information. Supervised classification has become expensive and time consuming as acquiring training sets for a large number of categories becomes more complex and classifiers are sensitive to data. Un-supervised classification has become an attractive alternative given it does not require training sets. However, un-superv ....Learning Specific Ontology for Un-Supervised Text Classification. The dramatic rise in massive text data has led to an increasing number of challenges in scalability and noisy information. Supervised classification has become expensive and time consuming as acquiring training sets for a large number of categories becomes more complex and classifiers are sensitive to data. Un-supervised classification has become an attractive alternative given it does not require training sets. However, un-supervised classification is still complex and there is a gap between understanding of concepts and features. This project aims to exploit domain ontology to find specific ontology which can bridge the gap, leading to a breakthrough for un-supervised classification. It provides foundations for classifying big text data.Read moreRead less
Opinion Analysis on Objects in Social Networks. This project seeks to provide a new integrated interactive data mining approach to analysing opinions on social networks, enabling organisations and individuals to make informed decisions based on qualitative as well as quantitative analysis. Social networks are fast becoming an important platform for understanding social opinions about events, organisations, products or services. Through an interactive analysis of social opinion, people can make b ....Opinion Analysis on Objects in Social Networks. This project seeks to provide a new integrated interactive data mining approach to analysing opinions on social networks, enabling organisations and individuals to make informed decisions based on qualitative as well as quantitative analysis. Social networks are fast becoming an important platform for understanding social opinions about events, organisations, products or services. Through an interactive analysis of social opinion, people can make better decisions. An ‘object’ in social networks refers to anything people talk about. This project aims to design and implement new social media mining algorithms to analyse the opinions that people express about such objects in terms of who, what, when and where.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
Discovery Early Career Researcher Award - Grant ID: DE220101379
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
Towards Transferable Visual Understanding in the Real World. This project aims to investigate how to improve the transferability of visual understanding algorithm and system in the real-world applications. This project expects to innovate and advance knowledge in the fields of visual transfer learning and generalizable visual representation learning. Expected outcomes of this project include techniques and algorithms to make the visual understanding system robust to diverse real-world scenarios. ....Towards Transferable Visual Understanding in the Real World. This project aims to investigate how to improve the transferability of visual understanding algorithm and system in the real-world applications. This project expects to innovate and advance knowledge in the fields of visual transfer learning and generalizable visual representation learning. Expected outcomes of this project include techniques and algorithms to make the visual understanding system robust to diverse real-world scenarios. This project should provide significant benefits, such as improving the robustness and safety of autonomous vehicles in transportation area, and reducing the cost of destructive data collection for intelligent fault detection in advanced manufacturing area.Read moreRead less