diff --git a/text/evaluation/main.tex b/text/evaluation/main.tex new file mode 100644 index 0000000..fc72d91 --- /dev/null +++ b/text/evaluation/main.tex @@ -0,0 +1,5 @@ +\chapter{Evaluation} +\label{ch:eval} + +\input{evaluation/thething} +\input{evaluation/theotherthing} diff --git a/text/evaluation/theotherthing.tex b/text/evaluation/theotherthing.tex new file mode 100644 index 0000000..188f303 --- /dev/null +++ b/text/evaluation/theotherthing.tex @@ -0,0 +1,2 @@ +\section{Selection of events} +\label{sec:lmdk-sel-eval} diff --git a/text/thething/evaluation.tex b/text/evaluation/thething.tex similarity index 97% rename from text/thething/evaluation.tex rename to text/evaluation/thething.tex index f44fafb..3b43a17 100644 --- a/text/thething/evaluation.tex +++ b/text/evaluation/thething.tex @@ -1,7 +1,8 @@ -\section{Evaluation} +\section{Significant events} \label{sec:lmdk-eval} -\kat{After discussing with Dimitris, I thought you are keeping one chapter for the proposals of the thesis. In this case, it would be more clean to keep the theoretical contributions in one chapter and the evaluation in a separate chapter. } +% \kat{After discussing with Dimitris, I thought you are keeping one chapter for the proposals of the thesis. In this case, it would be more clean to keep the theoretical contributions in one chapter and the evaluation in a separate chapter. } +% \mk{OK.} In this section we present the experiments that we performed on real and synthetic data sets. With the experiments on the synthetic data sets we show the privacy loss by our framework when tuning the size and statistical characteristics of the input {\thething} set $L$. We also show how the privacy loss under temporal correlation is affected by the number and distribution of the {\thethings}. diff --git a/text/main.tex b/text/main.tex index 502b125..fe7eab6 100644 --- a/text/main.tex +++ b/text/main.tex @@ -94,8 +94,8 @@ \input{introduction/main} \input{preliminaries/main} \input{related/main} -\input{thething/main} -\input{theotherthing/main} +\input{problem/main} +\input{evaluation/main} \input{conclusion/main} \backmatter diff --git a/text/problem/main.tex b/text/problem/main.tex new file mode 100644 index 0000000..c97cbd4 --- /dev/null +++ b/text/problem/main.tex @@ -0,0 +1,4 @@ +\chapter{The problem} + +\input{problem/thething/main} +\input{problem/theotherthing/main} diff --git a/text/problem/theotherthing/main.tex b/text/problem/theotherthing/main.tex new file mode 100644 index 0000000..4c72eda --- /dev/null +++ b/text/problem/theotherthing/main.tex @@ -0,0 +1,2 @@ +\section{Selection of events} +\label{sec:theotherthing} diff --git a/text/thething/contribution.tex b/text/problem/thething/contribution.tex similarity index 90% rename from text/thething/contribution.tex rename to text/problem/thething/contribution.tex index 266ff1c..64f16fd 100644 --- a/text/thething/contribution.tex +++ b/text/problem/thething/contribution.tex @@ -1,5 +1,5 @@ -\section{Contribution} -\label{sec:lmdk-contrib} +\subsection{Contribution} +\label{subsec:lmdk-contrib} In this chapter, 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. diff --git a/text/thething/main.tex b/text/problem/thething/main.tex similarity index 71% rename from text/thething/main.tex rename to text/problem/thething/main.tex index dd73547..b19fcf5 100644 --- a/text/thething/main.tex +++ b/text/problem/thething/main.tex @@ -1,11 +1,10 @@ -\chapter{Significant events} -\label{ch:thething} +\section{Significant events} +\label{sec:thething} In this chapter, we propose a novel configurable privacy scheme, \emph{\thething} privacy, which takes into account significant events (\emph{\thethings}) in the time series and allocates the available privacy budget accordingly. We propose two privacy models that guarantee {\thething} privacy and validate our proposal on real and synthetic data sets. \kat{Now, you have space so you need to be more detailed in the discussions, the motivation, the examples etc.} -\input{thething/motivation} -\input{thething/contribution} -\input{thething/problem} -\input{thething/evaluation} -\input{thething/summary} +\input{problem/thething/motivation} +\input{problem/thething/contribution} +\input{problem/thething/problem} +\input{problem/thething/summary} diff --git a/text/thething/motivation.tex b/text/problem/thething/motivation.tex similarity index 99% rename from text/thething/motivation.tex rename to text/problem/thething/motivation.tex index 7a0d588..3899f63 100644 --- a/text/thething/motivation.tex +++ b/text/problem/thething/motivation.tex @@ -1,5 +1,5 @@ -\section{Motivation} -\label{sec:lmdk-motiv} +\subsection{Motivation} +\label{subsec:lmdk-motiv} The plethora of sensors currently embedded in or paired with personal devices and other infrastructures have paved the way for the development of numerous \emph{crowdsensing services} (e.g.,~Google Maps~\cite{gmaps}, Waze~\cite{waze}, etc.) based on the collected personal, and usually geotagged and timestamped data. diff --git a/text/thething/problem.tex b/text/problem/thething/problem.tex similarity index 99% rename from text/thething/problem.tex rename to text/problem/thething/problem.tex index dab6ee7..435e79f 100644 --- a/text/thething/problem.tex +++ b/text/problem/thething/problem.tex @@ -1,5 +1,5 @@ -\section{{\Thething} privacy} -\label{sec:lmdk-prob} +\subsection{{\Thething} privacy} +\label{subsec:lmdk-prob} {\Thething} privacy is based on differential privacy. For this reason, we revisit the definition and important properties of differential privacy before moving on to the main ideas of this paper. @@ -7,7 +7,7 @@ Although, its local variant~\cite{duchi2013local} is more compatible with microd We refer the interested reader to~\cite{desfontaines2020sok} for a systematic taxonomy of the different variants and extensions of differential privacy, to~\cite{katsomallos2019privacy} for a survey of privacy models for continuous data publishing, and to~\cite{primault2018long} for an organization of the recent contributions in location privacy. -\subsection{Differential privacy} +\subsubsection{Differential privacy} \label{subsec:dp} \emph{Differential privacy}~\cite{dwork2006calibrating} is a property of a privacy mechanism $\mathcal{M}$ processing a set of \emph{privacy-sensitive} personal data $D$, @@ -55,7 +55,7 @@ results in $\mathcal{M}(D)$ with $\varepsilon = \varepsilon_1 + \varepsilon_2$. %Cao et al.~\cite{cao2017quantifying} propose a method for computing the total temporal privacy loss (TPL) in the presence of temporal correlations and background knowledge. Due to the lack of space, we refer the interested reader to the original publication for the complete definitions and formulas. -\subsection{Problem description and definition} +\subsubsection{Problem description and definition} \label{subsec:prob-set} %\kat{move flowchart here} diff --git a/text/thething/summary.tex b/text/problem/thething/summary.tex similarity index 90% rename from text/thething/summary.tex rename to text/problem/thething/summary.tex index b604246..f1e9468 100644 --- a/text/thething/summary.tex +++ b/text/problem/thething/summary.tex @@ -1,5 +1,5 @@ -\section{Summary and future work} -\label{sec:lmdk-sum} +\subsection{Summary and future work} +\label{subsec:lmdk-sum} 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 w.r.t. the traditional user-level differential privacy. We also proposed three models for {\thething} privacy, and quantified the privacy loss under temporal correlation. Our experiments on real and synthetic data sets validate our proposal. diff --git a/text/theotherthing/contribution.tex b/text/theotherthing/contribution.tex deleted file mode 100644 index 29ae8b1..0000000 --- a/text/theotherthing/contribution.tex +++ /dev/null @@ -1,2 +0,0 @@ -\section{Contribution} -\label{sec:lmdk-sel-contrib} diff --git a/text/theotherthing/evaluation.tex b/text/theotherthing/evaluation.tex deleted file mode 100644 index f005b9d..0000000 --- a/text/theotherthing/evaluation.tex +++ /dev/null @@ -1,2 +0,0 @@ -\section{Evaluation} -\label{sec:lmdk-sel-eval} diff --git a/text/theotherthing/main.tex b/text/theotherthing/main.tex deleted file mode 100644 index b8b5049..0000000 --- a/text/theotherthing/main.tex +++ /dev/null @@ -1,8 +0,0 @@ -\chapter{Privacy-preserving event significance} -\label{ch:theotherthing} - -\input{theotherthing/motivation} -\input{theotherthing/contribution} -\input{theotherthing/problem} -\input{theotherthing/evaluation} -\input{theotherthing/summary} diff --git a/text/theotherthing/motivation.tex b/text/theotherthing/motivation.tex deleted file mode 100644 index 6d6bd0b..0000000 --- a/text/theotherthing/motivation.tex +++ /dev/null @@ -1,2 +0,0 @@ -\section{Motivation} -\label{sec:lmdk-sel-motiv} diff --git a/text/theotherthing/problem.tex b/text/theotherthing/problem.tex deleted file mode 100644 index 4e29df2..0000000 --- a/text/theotherthing/problem.tex +++ /dev/null @@ -1,2 +0,0 @@ -\section{Privacy-preserving {\thething} selection} -\label{sec:lmdk-sel-prob} diff --git a/text/theotherthing/summary.tex b/text/theotherthing/summary.tex deleted file mode 100644 index 4301844..0000000 --- a/text/theotherthing/summary.tex +++ /dev/null @@ -1,2 +0,0 @@ -\section{Summary and future work} -\label{sec:lmdk-sel-sum}