tableDataAccess {DPpack}R Documentation

Differentially Private Contingency Table Data Access Function

Description

This function performs the data access step in the computation of a differentially private contingency table. The true values are computed using table,while the sensitivities are calculated based on bounded and unbounded differential privacy (Kifer and Machanavajjhala 2011) according to the theoretical values (Liu 2019).

Usage

tableDataAccess(..., mechanism = "Laplace")

Arguments

...

Vectors of data from which to create the contingency table.

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 contingency table 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

x <- MASS::Cars93$Type;
y <- MASS::Cars93$Origin;
tableDataAccess(x, y, mechanism='Laplace')


[Package DPpack version 0.2.2 Index]