期刊名称：Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications
印刷版ISSN：2093-5374
电子版ISSN：2093-5382
出版年度：2011
卷号：2
期号：1
页码：50-62
出版社：Innovative Information Science & Technology Research Group
摘要：Privacy is an increasingly important aspect of data publishing services. If personal private infor- mation is leaked from the data, the service will be regarded as unacceptable by the original owners of the data. Two different approaches to defining a notion of database privacy, the generalization method and the perturbation method, have been independently studied. These two approaches have significantly differences, making it hard to compare related research. In this paper, we propose a uni- fied model that is based on the perturbation method, but which is applicable to generalized data sets. In particular, this model applies the notion of differential privacy to data sets that satisfy k-anonymity. We demonstrate this approach through a simple case study. This is a first step towards a common notion for protecting database privacy
