Protecting Privacy of Sensitive Value Distributions in Data Release

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.