covDataAccess {DPpack}R Documentation

Differentially Private Covariance Data Access Function

Description

This function performs the data access step in the computation of a differentially private covariance. The true values are computed using cov, while the sensitivities are calculated based on bounded and unbounded differential privacy (Kifer and Machanavajjhala 2011) according to the theoretical values (Liu 2019). For the covariance, the sensitivities based on bounded and unbounded differential privacy are identical, so only one value is returned.

Usage

covDataAccess(x1, x2, lower.bound1, upper.bound1, lower.bound2, upper.bound2)

Arguments

x1, x2

Numeric vectors whose covariance is desired.

lower.bound1, lower.bound2

Real numbers giving the lower bounds of x1 and x2, respectively.

upper.bound1, upper.bound2

Real numbers giving the upper bounds of x1 and x2, respectively.

Value

List of the true covariance and the sensitivity calculated based on theoretical values.

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

covDataAccess(c(1,4,3,2), c(-2,-3,-4,-1), 0, 5, -5, 0)


[Package DPpack version 0.2.0 Index]