In this paper, disclosure risk assessment in Statistical Databases is performed by means of a probabilistic approach; in particular, we consider the problem of auditing databases that support statistical sum/count/mean/max/min queries to protect the privacy of sensitive boolean data. We provide both a theoretical framework for evaluating the disclosure risk and a tool for its control and management.
Quality & Quantity – Springer Journals
Published: Feb 12, 2015
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