Function opendp::measurements::make_base_discrete_laplace_cks20

source ·

pub fn make_base_discrete_laplace_cks20<D, QO>(
    scale: QO
) -> Fallible<Measurement<D, D::Carrier, D::InputMetric, MaxDivergence<QO>>>where
    D: DiscreteLaplaceDomain,
    D::Atom: Integer,
    (D, D::InputMetric): MetricSpace,
    QO: Float + InfCast<D::Atom>,
    Rational: TryFrom<QO>,
    Integer: From<D::Atom> + SaturatingCast<D::Atom>,

Expand description

Make a Measurement that adds noise from the discrete_laplace(scale) distribution to the input, using an efficient algorithm on rational bignums.

Set D to change the input data type and input metric:

`D`	input type	`D::InputMetric`
`AtomDomain<T>` (default)	`T`	`AbsoluteDistance<T>`
`VectorDomain<AtomDomain<T>>`	`Vec<T>`	`L1Distance<T>`

Citations

CKS20 The Discrete Gaussian for Differential Privacy

Arguments

scale - Noise scale parameter for the laplace distribution. scale == sqrt(2) * standard_deviation.

Generics

D - Domain of the data type to be privatized. Valid values are VectorDomain<AtomDomain<T>> or AtomDomain<T>
QO - Data type of the output distance and scale.