From a3cf9bf94e1bd95819dcdfb6d4d9e207b9000e39 Mon Sep 17 00:00:00 2001
From: Manos Katsomallos <manos@delkappa.com>
Date: Fri, 7 Jan 2022 01:09:19 +0100
Subject: [PATCH] katsomallos2022landmark: Updated the status

---
 text/bibliography.bib              | 2 +-
 text/conclusion/summary.tex        | 2 +-
 text/evaluation/main.tex           | 2 +-
 text/introduction/contribution.tex | 2 +-
 text/problem/main.tex              | 2 +-
 5 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/text/bibliography.bib b/text/bibliography.bib
index 50db20d..314073f 100644
--- a/text/bibliography.bib
+++ b/text/bibliography.bib
@@ -995,7 +995,7 @@
   author    = {Katsomallos, Manos and Tzompanaki, Katerina and Kotzinos, Dimitris},
   booktitle = {Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy},
   year      = {2022},
-  note      = {Under review}
+  note      = {To appear}
 }
 
 @inproceedings{kellaris2013practical,
diff --git a/text/conclusion/summary.tex b/text/conclusion/summary.tex
index f5af63a..2d46e96 100644
--- a/text/conclusion/summary.tex
+++ b/text/conclusion/summary.tex
@@ -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.
 \end{itemize}
 % \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}.
diff --git a/text/evaluation/main.tex b/text/evaluation/main.tex
index 7936483..b0336e4 100644
--- a/text/evaluation/main.tex
+++ b/text/evaluation/main.tex
@@ -1,6 +1,6 @@
 \chapter{Evaluation}
 \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.
 Section~\ref{sec:eval-dtl} contains all the details regarding the data sets the we used for our experiments along with the system configurations.
diff --git a/text/introduction/contribution.tex b/text/introduction/contribution.tex
index 58d6dfa..d545ab2 100644
--- a/text/introduction/contribution.tex
+++ b/text/introduction/contribution.tex
@@ -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},
 % \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}
 of the $12$th ACM conference on Data and Application Security and Privacy.
diff --git a/text/problem/main.tex b/text/problem/main.tex
index 5734ce3..4311bf9 100644
--- a/text/problem/main.tex
+++ b/text/problem/main.tex
@@ -1,6 +1,6 @@
 \chapter{{\Thething} privacy}
 \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
 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.