Boosting the Accuracy of Differentially Private Histograms Through Consistency

  title={Boosting the Accuracy of Differentially Private Histograms Through Consistency},
  author={Michael Hay and Vibhor Rastogi and Gerome Miklau and Dan Suciu},
We show that it is possible to significantly improve the accuracy of a general class of histogram queries while satisfying differential privacy. Our approach carefully chooses a set of queries to evaluate, and then exploits consistency constraints that should hold over the noisy output. In a postprocessing phase, we compute the consistent input most likely to have produced the noisy output. The final output is differentially-private and consistent, but in addition, it is often much more… CONTINUE READING
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