2011 | OriginalPaper | Buchkapitel
Protecting Privacy of Sensitive Value Distributions in Data Release
verfasst von : Michele Bezzi, Sabrina De Capitani di Vimercati, Giovanni Livraga, Pierangela Samarati
Erschienen in: Security and Trust Management
Verlag: Springer Berlin Heidelberg
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In today’s electronic society, data sharing and dissemination are more and more increasing, leading to concerns about the proper protection of privacy. In this paper, we address a novel privacy problem that arises when non sensitive information is incrementally released and sensitive information can be inferred exploiting dependencies of sensitive information on the released data. We propose a model capturing this inference problem where sensitive information is characterized by peculiar distributions of non sensitive released data. We also discuss possible approaches for run time enforcement of safe releases.