Database Reference
In-Depth Information
Chapter 18
Quantifying the Privacy of Exact Hiding
Algorithms
The exact hiding algorithms that were presented in Chapters 14, 15, and 16 are all
based on the principle of minimum harm (distortion), which requires the minimum
amount of modifications to be made to the original database to facilitate sensitive
knowledge hiding. As an effect, in most cases (depending on the problem instance
at hand), the sensitive itemsets are expected to be positioned just below the revised
borderline in the computed sanitized database D. However, the selection of the min-
imum support threshold based on which the hiding is performed can lead to radi-
cally different solutions, some of which are bound to be superior to others in terms
of offered privacy. In this chapter, we present a layered approach that was originally
proposed in [27], which enables the owner of the data to quantify the privacy that
is offered on a given database by the employed exact hiding algorithm. Assuming
that an adversary has no knowledge regarding which of the infrequent itemsets in D
are the sensitive ones, this approach can compute the disclosure probability for the
hidden sensitive itemsets, given the sanitized database D and a minimum support or
frequency threshold msup/mfreq.
Search WWH ::




Custom Search