privacy: Reference to the local variant of dp
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@ -177,6 +177,9 @@ The privacy budget $\varepsilon$ is a positive real number that represents the u
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As the definition implies, $\mathcal{M}$ achieves stronger privacy protection for lower values of $\varepsilon$ since the probabilities of $D$ and $D'$ being true worlds are similar, but the utility of $\pmb{o}$ is reduced since more randomness is introduced by $\mathcal{M}$.
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As the definition implies, $\mathcal{M}$ achieves stronger privacy protection for lower values of $\varepsilon$ since the probabilities of $D$ and $D'$ being true worlds are similar, but the utility of $\pmb{o}$ is reduced since more randomness is introduced by $\mathcal{M}$.
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The privacy budget $\varepsilon$ is usually set to $0.01$, $0.1$, or, in some cases, $\ln2$ or $\ln3$~\cite{lee2011much}.
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The privacy budget $\varepsilon$ is usually set to $0.01$, $0.1$, or, in some cases, $\ln2$ or $\ln3$~\cite{lee2011much}.
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Its local variant~\cite{duchi2013local} is compatible with microdata, where $D$ is composed of a single data item $x$.
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We refer the interested reader to~\cite{desfontaines2020sok} for a systematic taxonomy of the different variants and extensions of differential privacy.
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\begin{definition}
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\begin{definition}
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[Query function sensitivity]
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[Query function sensitivity]
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\label{def:qry-sens}
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\label{def:qry-sens}
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