Preprints‎ > ‎

A Bayesian approach for on-line Sum/Count/Max/Min Auditing on boolean data by Bice Cavallo and Gerardo Canfora

pubblicato 09 lug 2012, 03:09 da Gerardo Canfora
We consider the problem of auditing databases that support statistical sum/count/max/min queries to protect the privacy of sensitive information. We study the case in which the domain of the sensitive information is the boolean set. Principles and techniques developed for the privacy of statistical databases in the case of continuous attributes do not always apply here. We provide a probabilistic framework for the on-line auditing and we show that sum/count/min/max queries can be audited by means of a Bayesian network.
Privacy in Statistical Databases (PSD 2012)
Gerardo Canfora,
09 lug 2012, 03:09