Job Birth Postcode Illness Cat 1 1975 4350 HIV Cat

Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a more sophisticated model is necessary to protect the association of individuals to sensitive information. In this paper, we propose an (α, k)-anonymity model to protect both identifications and relationships to sensitive information in data. We discuss the properties of (α, k)-anonymity model. We prove that the optimal (α, k)-anonymity problem is NP-hard. We first present an optimal global-recoding method for the (α, k)-anonymity problem. Next we propose two scalable local-recoding algorithms which are both more scalable and result in less data Raymond Chi-Wing Wong Department of Computer Science and Engineering Hong Kong University of Science and Technology Jiuyong Li School of Computer and Information Sciences University of South Australia Ada Wai-Chee Fu Department of Computer Science and Engineering Chinese university of Hong Kong Ke wang Department of Computer Science Simon Fraser University, Canada