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katsomallos2022landmark: Updated the status

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Manos Katsomallos 2022-01-07 01:09:19 +01:00
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text/bibliography.bib
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@ -995,7 +995,7 @@
author = {Katsomallos, Manos and Tzompanaki, Katerina and Kotzinos, Dimitris}, author = {Katsomallos, Manos and Tzompanaki, Katerina and Kotzinos, Dimitris},
booktitle = {Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy}, booktitle = {Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy},
year = {2022}, year = {2022},
note = {Under review} note = {To appear}
} }
@inproceedings{kellaris2013practical, @inproceedings{kellaris2013practical,

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text/conclusion/summary.tex
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@ -31,4 +31,4 @@ We presented ($\varepsilon$, $L$)-\emph{{\thething} privacy}, a novel privacy no
We showed that our methodology can provide adequate differential privacy guarantees while achieving better data utility than the user-level scheme. We showed that our methodology can provide adequate differential privacy guarantees while achieving better data utility than the user-level scheme.
\end{itemize} \end{itemize}
% \kat{mention here again that the work appears in the article... submitted at...} % \kat{mention here again that the work appears in the article... submitted at...}
This work is under review for being published in the proceedings of the $12$th ACM conference on Data and Application Security and Privacy~\cite{katsomallos2022landmark}. This work will appear in the proceedings of the $12$th ACM conference on Data and Application Security and Privacy~\cite{katsomallos2022landmark}.

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text/evaluation/main.tex
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@ -1,6 +1,6 @@
\chapter{Evaluation} \chapter{Evaluation}
\label{ch:eval} \label{ch:eval}
\nnfootnote{This chapter is under review for being published in the proceedings of the $12$th ACM conference on Data and Application Security and Privacy~\cite{katsomallos2022landmark}.\bigskip} \nnfootnote{This chapter will appear in the proceedings of the $12$th ACM conference on Data and Application Security and Privacy~\cite{katsomallos2022landmark}.\bigskip}
In this chapter, we present the experiments that we performed in order to evaluate {\thething} privacy (Chapter~\ref{ch:lmdk-prv}) on real and synthetic data sets. In this chapter, we present the experiments that we performed in order to evaluate {\thething} privacy (Chapter~\ref{ch:lmdk-prv}) on real and synthetic data sets.
Section~\ref{sec:eval-dtl} contains all the details regarding the data sets the we used for our experiments along with the system configurations. Section~\ref{sec:eval-dtl} contains all the details regarding the data sets the we used for our experiments along with the system configurations.

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text/introduction/contribution.tex
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@ -44,6 +44,6 @@ Furthermore, we estimate the impact of the privacy-preserving dummy {\thething}
The second and the third contributions are described in the article~\cite{katsomallos2022landmark}, The second and the third contributions are described in the article~\cite{katsomallos2022landmark},
% \kat{cite the technical report} % \kat{cite the technical report}
which is submitted at the research papers track which will appear at the research papers track
% \kat{name the conference} % \kat{name the conference}
of the $12$th ACM conference on Data and Application Security and Privacy. of the $12$th ACM conference on Data and Application Security and Privacy.

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text/problem/main.tex
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@ -1,6 +1,6 @@
\chapter{{\Thething} privacy} \chapter{{\Thething} privacy}
\label{ch:lmdk-prv} \label{ch:lmdk-prv}
\nnfootnote{This chapter is under review for being published in the proceedings of the $12$th ACM conference on Data and Application Security and Privacy~\cite{katsomallos2022landmark}.} \nnfootnote{This chapter will appear in the proceedings of the $12$th ACM conference on Data and Application Security and Privacy~\cite{katsomallos2022landmark}.}
% Crowdsensing applications % Crowdsensing applications
The plethora of sensors currently embedded in personal devices and other infrastructures have paved the way for the development of numerous \emph{crowdsensing services} (e.g.,~Ring~\cite{ring}, TousAntiCovid~\cite{tousanticovid}, Waze~\cite{waze}, etc.) based on the collected personal, and usually geotagged and timestamped data. The plethora of sensors currently embedded in personal devices and other infrastructures have paved the way for the development of numerous \emph{crowdsensing services} (e.g.,~Ring~\cite{ring}, TousAntiCovid~\cite{tousanticovid}, Waze~\cite{waze}, etc.) based on the collected personal, and usually geotagged and timestamped data.