add_laplace_noise

Adds Laplace-distributed noise to a numeric value or vector for differential privacy.
The Laplace mechanism is typically used for queries with sensitivity based on the
maximum absolute difference a single record can make.

internal

A tidy-style interface for applying differential privacy to data frames.
Provides pipe-friendly functions to add calibrated noise, compute private statistics,
and track privacy budgets using the epsilon-delta differential privacy framework.
Implements the Laplace mechanism (Dwork et al. 2006 <doi:10.1007/11681878_14>) and
the Gaussian mechanism for achieving differential privacy as described in Dwork and
Roth (2014) <doi:10.1561/0400000042>.

Thomas Tarler

tidydp

Tidy Differential Privacy

add_laplace_noise function

<dl><dt>x</dt>
<dd>Numeric value or vector to add noise to</dd>
<dt>sensitivity</dt>
<dd>The sensitivity of the query (maximum change from one record)</dd>
<dt>epsilon</dt>
<dd>Privacy parameter (smaller = more privacy, more noise)</dd></dl>

Arguments

Add Laplace Noise — add_laplace_noise

<dl>

<dt>x</dt>
<dd>Numeric value or vector to add noise to</dd>


<dt>sensitivity</dt>
<dd>The sensitivity of the query (maximum change from one record)</dd>


<dt>epsilon</dt>
<dd>Privacy parameter (smaller = more privacy, more noise)</dd>

</dl>

add_laplace_noise: Add Laplace Noise

Description

Usage

Value

Arguments