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statistical: Correction on wang2018privacy

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Manos Katsomallos 2021-09-06 18:22:48 +03:00
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tables/statistical.tex
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@ -78,8 +78,8 @@
\hyperlink{chen2017pegasus}{\emph{PeGaSus}} & infinite & streaming & global & event & linkage & perturbation & differential \\ \hyperlink{chen2017pegasus}{\emph{PeGaSus}} & infinite & streaming & global & event & linkage & perturbation & differential \\
\cite{chen2017pegasus} & & & & & & (Laplace) & privacy \\ \hdashline \cite{chen2017pegasus} & & & & & & (Laplace) & privacy \\ \hdashline
\hyperlink{wang2018privacy}{\textbf{\emph{DP-PSP}}} & infinite & streaming & global & $w$-event & linkage & perturbation & differential \\ \hyperlink{wang2018privacy}{\textbf{\emph{DP-PSP}}} & infinite & streaming & global & $w$-event & linkage & perturbation (ex- & differential \\
\cite{wang2018privacy} & & & & & & (Laplace) & privacy \\ \cite{wang2018privacy} & & & & & & ponential, Laplace) & privacy \\
\hyperlink{ma2019real}{\textbf{\emph{RPTR}}} & infinite & streaming & global & $w$-event & linkage & perturbation & differential \\ \hyperlink{ma2019real}{\textbf{\emph{RPTR}}} & infinite & streaming & global & $w$-event & linkage & perturbation & differential \\
\cite{ma2019real} & & & & & & (Laplace) & privacy \\ \hdashline \cite{ma2019real} & & & & & & (Laplace) & privacy \\ \hdashline

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text/related/statistical.tex
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@ -363,7 +363,7 @@ The combination of the Perturber and the Grouper follows the sequential composit
% - global % - global
% - w-event % - w-event
% - differential privacy % - differential privacy
% - perturbation (Laplace) % - perturbation (exponential, Laplace)
\hypertarget{wang2018privacy}{Wang et al.}~\cite{wang2018privacy} presented \emph{DP-PSP}, an approach for publishing differentially private statistics over infinite streams of trajectory data. \hypertarget{wang2018privacy}{Wang et al.}~\cite{wang2018privacy} presented \emph{DP-PSP}, an approach for publishing differentially private statistics over infinite streams of trajectory data.
DP-PSP segments trajectories by taking into account points of interest in road networks. DP-PSP segments trajectories by taking into account points of interest in road networks.
A start and end point (anchor) represents a segment and each data point in the trajectory data is calibrated to the nearest anchor. A start and end point (anchor) represents a segment and each data point in the trajectory data is calibrated to the nearest anchor.