School of Computer and Information Science, University of South Australia, Adelaide
Jiuyong Li received his PhD degree in computer science from Griffith University in Australia. He is currently an associate professor at University of South Australia. He was a lecturer and senor lecturer at the University of Southern Queensland in Australia. His main research interests are in data mining, privacy preservation and Bioinformatics. He has published intensively in data mining area. His research has been supported by two Australian Research Council Discovery grants. He was a co-general chair of Australasian Data Mining Conference in 2006 and 2007.
Department of Mathematics and Computing, University of Southern Queensland, Toowoomba
Hua Wang is a Senior Lecture in University of Southern Queensland, Australia. Dr Wang received his PhD degree in computer science from The University of Southern Queensland in 2004. He has been active in the areas of Data Mining, Information Systems Management, Access Control, Software Engineering and Electronic Commerce. He has participated in research projects on mobile electronic system, Web service, and role-based access control for Electronic service system. He has published more than 60 research papers in refereed international journals and conference proceedings. Dr Wang has been reserved as a technical PC member of ACSC since 2005. He is the publicity Co-Chair of APWEB2008.
NICTA Canberra Lab, Canberra ACT, Australia
Huidong Jin received his B.Sc. and M.Sc. degrees from the Department of Applied Mathematics in 1995, and his M.Sc. degree from the Institute of Information and System Sciences in 1998, both from Xi'an Jiaotong University, P.R. China. In 2002, he got his Ph.D degree in Computer Science and Engineering from the Chinese University of Hong Kong, Shatin, Hong Kong. He is currently a reseacher at NICTA Canberra Lab and an adjunct research fellow at the Australian National University, Canberra, Australia. His research interests include data mining, health informatics, information retrieval, security and privacy. He has authored or co-authored over 30 papers in these areas
School of Information Systems, University of Southern Queensland, Toowoomba
Current Developments of k-Anonymous Data Releasing
Jiuyong Li, Hua Wang, Huidong Jin, Jianming Yong
Disclosure-control is a traditional statistical methodology for protecting privacy when data is released for analysis. Disclosure-control methods have enjoyed a revival in the data mining community, especially after the introduction of the k-anonymity model by Samarati and Sweeney. Algorithmic advances on k-anonymisation provide simple and effective approaches to protect private information of individuals via only releasing k-anonymous views of a data set. Thus, the kanonymity model has gained increasing popularity. Recent research identifies some drawbacks of the k-anonymity model and presents enhanced k-anonymity models. This paper reviews problems of the k-anonymity model and its enhanced variants, and different methods for implementing k-anonymity. It compares the k-anonymity model with the secure multiparty computation-based privacy-preserving techniques in the data mining literature. The paper also discusses further development directions of the k-anonymous data releasing.