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Manos Katsomallos
2021-10-22 16:28:55 +02:00
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\section{Summary}
\label{sec:lmdk-sum}
\nnfootnote{This chapter was published in the proceedings of the $19$th Journal of Spatial Information Science~\cite{katsomallos2019privacy}.}
In this chapter, we presented \emph{{\thething} privacy} for privacy-preserving time series publishing, which allows for the protection of significant events, while improving the utility of the final result with respect to the traditional user-level differential privacy.
We also proposed three models for {\thething} privacy, and quantified the privacy loss under temporal correlation.