spend_privacy_budget

Records a privacy expenditure and updates the budget

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

spend_privacy_budget function

<dl><dt>budget</dt>
<dd>A privacy budget object</dd>
<dt>epsilon_spent</dt>
<dd>Epsilon spent on the operation</dd>
<dt>delta_spent</dt>
<dd>Delta spent on the operation (default: 0)</dd>
<dt>operation_name</dt>
<dd>Name/description of the operation (optional)</dd></dl>

Arguments

Spend Privacy Budget — spend_privacy_budget

<dl>

<dt>budget</dt>
<dd>A privacy budget object</dd>


<dt>epsilon_spent</dt>
<dd>Epsilon spent on the operation</dd>


<dt>delta_spent</dt>
<dd>Delta spent on the operation (default: 0)</dd>


<dt>operation_name</dt>
<dd>Name/description of the operation (optional)</dd>

</dl>

spend_privacy_budget: Spend Privacy Budget

Description

Usage

Value

Arguments