Reviewed ou2018optimal

text/related/micro.tex

@@ -274,6 +274,22 @@ private and eligible for publishing.
 The authors compare their design with that of~\cite{chen2012differentially} and~\cite{he2015dpt} by running several tests, and ascertain that it outperforms them in terms of data utility.
 However, due to DP-Star's privacy budget distribution to its different phases, for small values of $\varepsilon$ the framework's privacy performance is inferior to that of its competitors.
 
+% An Optimal Pufferfish Privacy Mechanism for Temporally Correlated Trajectories
+% - microdata
+% - finite (sequential)
+% - batch
+% - dependence (temporal)
+% - local
+% - event
+% - differential privacy
+% - perturbation (randomized response, Laplace)
+\hypertarget{ou2018optimal}{Ou et al.}~\cite{ou2018optimal} designed \emph{FGS-Pufferfish} for publishing temporally correlated trajectory data while protecting temporal correlation.
+FGS-Pufferfish transforms a user's daily trajectories into a set of sine and cosine waves of different frequencies along with the corresponding Fourier coefficients.
+Then, it adds Laplace noise to the Fourier coefficients' geometric sum. 
+The authors obtain the optimal noisy Fourier coefficients by solving the constrained optimization problem via the Lagrange Multiplier method depending on the available privacy budget. 
+They evaluate both the location data utility and the temporal correlation utility.
+The experimental evaluation shows that FGS-Pufferfish outperforms CTS-DP~\cite{wang2017cts} in terms of the trade-off between privacy and location utility.
+
 
 \subsection{Infinite observation}
 \label{subsec:micro-infinite}
@@ -422,7 +438,7 @@ Last but not least, the technique requires the calculation of the temporal priva
 % ON-OFF Privacy in the Presence of Correlation
 % ON-OFF Privacy Against Correlation Over Time
 % - microdata
-% - infinite
+% - infinite (sequential)
 % - streaming
 % - dependence
 % - event