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EDBT
2008
ACM

A Bayesian approach for on-line max and min auditing

14 years 3 months ago
A Bayesian approach for on-line max and min auditing
In this paper we consider the on-line max and min query auditing problem: given a private association between fields in a data set, a sequence of max and min queries that have already been posed about the data, their corresponding answers and a new query, deny the answer if a private information is inferred or give the true answer otherwise. We give a probabilistic definition of privacy and demonstrate that max and min queries, without "no duplicates"assumption, can be audited by means of a Bayesian network. Moreover, we show how our auditing approach is able to manage user prior-knowledge. Keywords Bayesian network, Statistical database, Auditing
Gerardo Canfora, Bice Cavallo
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2008
Where EDBT
Authors Gerardo Canfora, Bice Cavallo
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