covDataAccess {DPpack} | R Documentation |
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.
covDataAccess(x1, x2, lower.bound1, upper.bound1, lower.bound2, upper.bound2)
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. |
List of the true covariance and the sensitivity calculated based on theoretical values.
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.
covDataAccess(c(1,4,3,2), c(-2,-3,-4,-1), 0, 5, -5, 0)