problem: Minor corrections

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Manos Katsomallos 2021-10-15 09:02:12 +02:00
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@ -39,8 +39,8 @@ Event-level limits the privacy protection to \emph{any single event}, user-level
\kat{Please write another introduction for your chapter, that is in connection to your thesis, not the paper.. all this information in this paragraph must be said in the introduction of the thesis, not of the chapter.. }
In this chapter, we propose a novel configurable privacy scheme, \emph{\thething} privacy (Section~\ref{sec:thething}), which takes into account significant events (\emph{\thethings}) in the time series and allocates the available privacy budget accordingly.
We propose three privacy models that guarantee {\thething} privacy.
To further enhance our privacy method, and protect the {\thethings} position in the time series, we propose techniques to perturb the initial {\thethings} set (Section~\ref{sec:theotherthing}).\kat{this is the content that you must enrich and motivate more in the intro of this chapter}
We propose three privacy schemes that guarantee {\thething} privacy.
To further enhance our privacy methodology, and protect the {\thethings} position in the time series, we propose techniques to perturb the initial {\thethings} set (Section~\ref{sec:theotherthing}).\kat{this is the content that you must enrich and motivate more in the intro of this chapter}
\input{problem/thething/main}
\input{problem/theotherthing/main}

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@ -2,5 +2,5 @@
\label{subsec:lmdk-contrib}
In this section, we formally define a novel privacy notion that we call \emph{{\thething} privacy}.
We apply this privacy notion to time series consisting of \emph{{\thethings}} and regular events, and we design and implement three {\thething} privacy mechanisms.
We apply this privacy notion to time series consisting of \emph{{\thethings}} and regular events, and we design and implement three {\thething} privacy schemes.
We further study {\thething} privacy under temporal correlation that is inherent in time series publishing.