Abstract
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.
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Bezzi, M., De Capitani di Vimercati, S., Livraga, G., Samarati, P. (2011). Protecting Privacy of Sensitive Value Distributions in Data Release. In: Cuellar, J., Lopez, J., Barthe, G., Pretschner, A. (eds) Security and Trust Management. STM 2010. Lecture Notes in Computer Science, vol 6710. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22444-7_17
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DOI: https://doi.org/10.1007/978-3-642-22444-7_17
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