XML Views of Relational Databases: Semantics and Update Problems. XML is the standard for representing, publishing and exchanging data over the Internet and relational database is the dominant technology for data management. Updating XML views over relational data is fundamental to bring these two technologies together to serve Internet-based applications. Australia has been a leading country in both developing and applying internet technologies. The theoretic outcomes of this project will contr ....XML Views of Relational Databases: Semantics and Update Problems. XML is the standard for representing, publishing and exchanging data over the Internet and relational database is the dominant technology for data management. Updating XML views over relational data is fundamental to bring these two technologies together to serve Internet-based applications. Australia has been a leading country in both developing and applying internet technologies. The theoretic outcomes of this project will contribute to the advance in database and web research communities and establish us as an internationally leading group in this research area. The technological outcomes will help organisations in Australia effectively and efficiently conduct e-Business on the Internet. Read moreRead less
Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less
Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the mod ....Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the model, In particular, the project plans to investigate flexible social network query methods to make users’ event search easy. Finally the project plans to build an evaluation system to demonstrate the efficiency of the algorithms and effectiveness of the model.Read moreRead less
Biclique discovery in Big Data. This project aims to design algorithms to capture Big Data. Biclique is a popular graph model that can capture important cohesive structures in many applications. However, traditional biclique discovery algorithms which only focus on simple, small-scale, static and deterministic data are inadequate in the era of Big Data where data has Variety (various formats), Volume (large quantity), Velocity (dynamic update) and Veracity (uncertainty). This project expects to ....Biclique discovery in Big Data. This project aims to design algorithms to capture Big Data. Biclique is a popular graph model that can capture important cohesive structures in many applications. However, traditional biclique discovery algorithms which only focus on simple, small-scale, static and deterministic data are inadequate in the era of Big Data where data has Variety (various formats), Volume (large quantity), Velocity (dynamic update) and Veracity (uncertainty). This project expects to benefit real applications in both public and private sectors and add value to Australian manufactured products.Read moreRead less
Analysis and classification of malicious code. Malicious software such as viruses and worms directly attacks the security, privacy and integrity of Australian e-commerce, large databases and communication channels. The recent uptake of malicious software by organised crime has made finding effective countermeasures more urgent. Around 80% of the malicious code in circulation is disguised in some way. This significantly increases the difficulty of automated detection and delays analysis. Automate ....Analysis and classification of malicious code. Malicious software such as viruses and worms directly attacks the security, privacy and integrity of Australian e-commerce, large databases and communication channels. The recent uptake of malicious software by organised crime has made finding effective countermeasures more urgent. Around 80% of the malicious code in circulation is disguised in some way. This significantly increases the difficulty of automated detection and delays analysis. Automated classification and de-obfuscation technologies are a precondition to applying more sophisticated detection heuristics. The project will be instrumental in safeguarding Australia by protecting critical infrastructure and defending us from online organised crime and information warfare.Read moreRead less
Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and ....Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and efficient algorithms for searching and monitoring cohesive subgraphs in big and dynamic attributed graphs from both structure and attribute perspectives. The methods, techniques, and prototype systems developed in this project can be deployed to facilitate the smart use of big graph data across the nation. Read moreRead less
Information security and digital watermarking with Latin squares. The importance of digital information is increasing constantly. Audio, video, and still image data dominate our daily lives. Such information has commercial and strategic importance. It is invaluable in crime prevention: for example, video from security cameras. The protection of commercially valuable material against piracy and sensitive information against security breaches is vital to our economy and our safety. This project ad ....Information security and digital watermarking with Latin squares. The importance of digital information is increasing constantly. Audio, video, and still image data dominate our daily lives. Such information has commercial and strategic importance. It is invaluable in crime prevention: for example, video from security cameras. The protection of commercially valuable material against piracy and sensitive information against security breaches is vital to our economy and our safety. This project addresses these issues, by developing new, secure watermarks and fingerprints to protect digital information. Such watermarks can also protect radio communication channels, which is important due to the rising demand for wireless connectivity.Read moreRead less
Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for differen ....Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for different applications and devise efficient algorithms for searching and monitoring those cohesive groups based on different models. The methods, techniques, and evaluation systems developed in this project can be deployed to facilitate the smart use of heterogeneous information networks across the nation.Read moreRead less
Privacy-Preserving Location Based Queries. This project aims to develop efficient solutions for mobile users to consume location-based services (LBS) without revealing their locations. The project expects to demonstrate the effectiveness of the solutions using theoretic analysis and practical experiments. The expected outcomes are a multiparty trust model, techniques to distribute user location information among multiple location-based services, and a practical system to protect privacy in mobil ....Privacy-Preserving Location Based Queries. This project aims to develop efficient solutions for mobile users to consume location-based services (LBS) without revealing their locations. The project expects to demonstrate the effectiveness of the solutions using theoretic analysis and practical experiments. The expected outcomes are a multiparty trust model, techniques to distribute user location information among multiple location-based services, and a practical system to protect privacy in mobile environments. This should protect the privacy of individuals and increase users’ trust in location-based systems.Read moreRead less
Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results th ....Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results that depend on the perceived state of the querier. This project will develop indexing and search techniques for massive structured data sets. The new search methods will incorporate theoretical advances and will be experimentally validated using industry-standard open-source distributed systems.Read moreRead less