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')