Security

CAI conducts research that applies to information security, law enforcement and defence initiatives. Below are some of our current security projects.

Protect information sharing within distributed collaborative environment

Information sharing on distributed collaboration usually occurs in broad, highly dynamic network-based environments, and formally accessing the resources in a secure manner poses a difficult and vital challenge. This project develops a systematic methodology for information sharing in distributed collaborative environments. It will ensure sensitive information and information assurance requirements, and incorporate new security constrains and policies raised by emerging technologies. We will create a new rule-based framework to identify and address issues of sharing in collaborative environments; and to specify and enforce security rules to support identified issues while minimizing the risks of information sharing through the framework.

This project was supported by Australian Research Council (ARC) Discover Project (DP0988465).

Research team

Professor Hua Wang, CAI, VU

Privacy preserving data sharing in data mining environments

Preserving privacy in data mining among various enterprises and organisations is essential for many real world applications in areas like health surveillance, business analysis, fraud detection and terror protection. Efficient and effective techniques are badly needed to protect privacy in data sharing and data mining. The developed cutting-edge techniques in this project will be implemented in freely available open source software tools, empowering Australian organisations to utilise the techniques to develop intelligent systems in data sharing environments. These techniques will ultimately lead to better utilisation of the information available in many enterprises and organisations.

This project was supported by Australian Research Council (ARC) Discover Project (DP0663414).

Research team

Professor Jiuyong Li, UniSA

Professor Hua Wang, CAI, VU

Limiting disclosure of private information in relational database systems

Enterprises are deeply concerned about customers' privacy issues and try to build solid trust to attract customers. This project continues development of new purpose-based frameworks and private information assurance requirements in relational database systems. The frameworks will identify and address issues of protecting private information; and to specify and enforce privacy rules to support identified issues. It aims to develop techniques for purpose-based usage control and detecting possible conflicts between obligations. The approach leads to a great understanding of advocating limited disclosure in usage control systems. The project develops fundamental enabling methodologies for the information and communication industry.

This project was supported by Australian Research Council (ARC) Discover Project (DP0988465).

Research team

Professor Hua Wang, CAI, VU

Privacy protection in distributed data mining and data warehouse query

Information and Communications Technology (ICT) has dramatically altered the world's social and economic landscape. 'From data to knowledge' is one of the priority challenges recognised by National ICT Australia. However, privacy concerns may prevent it from realisation. This project aims to fulfil 'from data to knowledge' without breaching privacy of data from distributed resources held by different parties. The outcomes of this project will create new directions in the research of privacy‑preserving distributed data mining and are applicable to Australian counter‑terrorism and homeland defence in detecting bio‑terrorism from privacy sensitive data.

This project was supported by Australian Research Council (ARC) Discover Project (2007-2009) and ARC Discover Project (2009-2011).

Research team

Professor Hua Wang, CAI, VU

Professor Yanchun Zhang, Director CAI, VU

Professor Eiji Okamoto, University of Tsukuba

Private searching on streaming data

Private searching on streaming data is a process to dispatch a program to a public server. The program searches streaming sources of data without revealing searching criteria and then returns a buffer containing the findings.

From an Abelian group homomorphic encryption, the searching criteria can be constructed by only simple combinations of keywords, e.g., disjunction of keywords. The recent breakthrough in fully homomorphic encryption has allowed us to construct arbitrary searching criteria theoretically. In this research, we consider a (t,n) threshold query, which searches for documents containing more than t out of n keywords. This form of query can help us find more relevant documents.

We have constructed the searching criteria for private threshold searching on streaming data on the basis of the state-of-the-art fully homomorphic encryption techniques. Our protocol is semantically secure as long as the underlying fully homomorphic encryption scheme is semantically secure.

Research team

Professor Hua Wang, CAI, VU

Private protection for location-based queries

In this research, we have given a solution to one of the location-based query problems.

This problem is defined as follows:
(i) a user wants to query a database of location data, known as Points Of Interest (POI), and does not want to reveal his/her location to the server due to privacy concerns.
(ii) the owner of the location data, that is, the location server, does not want to simply distribute its data to all users.

The location server desires to have some control over its data, since the data is its asset. Previous solutions have used a trusted anonymiser to address privacy, but introduced the impracticality of trusting a third party. More recent solutions have used homomorphic encryption to remove this weakness. Briefly, the user submits his/her encrypted coordinates to the server and the server would determine the user's location homomorphically, and then the user would acquire the corresponding record using Private Information Retrieval techniques.

We have proposed a major enhancement upon this result by introducing a similar two stage approach, where the homomorphic comparison step is replaced with Oblivious Transfer to achieve a more secure solution for both parties. Our solution is efficient and practical in many scenarios.

Research team

Professor Hua Wang, CAI, VU