histogramDataAccess {DPpack} | R Documentation |
Differentially Private Histogram Data Access Function
Description
This function performs the data access step in the computation of a
differentially private histogram. The true values are computed using
hist
, while the sensitivities are calculated based on
bounded and unbounded differential privacy (Kifer and Machanavajjhala 2011)
according to the theoretical values (Liu 2019).
Usage
histogramDataAccess(x, breaks, mechanism)
Arguments
x |
Numeric vector from which the histogram will be formed.. |
breaks |
Identical to the argument with the same name from
|
mechanism |
String indicating which mechanism to use for differential privacy. If the 'Laplace' mechanism is chosen, l1 sensitivities are returned. If the 'Gaussian' or 'analytic' mechanisms are chosen, l2 sensitivities are returned. |
Value
List of the true histogram and the sensitivities calculated based on bounded and unbounded differential privacy.
References
Liu F (2019). “Statistical Properties of Sanitized Results from Differentially Private Laplace Mechanism with Univariate Bounding Constraints.” Transactions on Data Privacy, 12(3), 169-195. http://www.tdp.cat/issues16/tdp.a316a18.pdf.
Kifer D, Machanavajjhala A (2011). “No Free Lunch in Data Privacy.” In Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data, SIGMOD '11, 193–204. ISBN 9781450306614, doi:10.1145/1989323.1989345.
Examples
histogramDataAccess(c(1,4,3,2,3), 'Sturges', 'Laplace')