related: Minor corrections

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Manos Katsomallos 2021-10-15 09:02:44 +02:00
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@ -16,8 +16,8 @@ Finally, there are some surveys on application-specific privacy challenges.
For example, Zhou et al.~\cite{zhou2008brief} have a focus on social networks, and Christin et al.~\cite{christin2011survey} give an outline of how privacy aspects are addressed in crowdsensing applications.
In this chapter, we document works that deal with privacy under continuous data publishing covering diverse use cases.
We present the works in the literature based on two levels of categorisation.
First, we group works with respect to whether they receive microdata or statistical data (see Section~\ref{subsec:data-categories} for the definitions) as input.
We present the works in the literature based on two levels of categorization.
First, we group works with respect to whether they deal with microdata or statistical data (see Section~\ref{subsec:data-categories} for the definitions) as input.
Then, we further group them into two subcategories, whether they are designed for the finite or infinite (see Section.~\ref{subsec:data-publishing}) observation setting. \kat{continue.. say also in which category you place your work}
%Such a documentation becomes very useful nowadays, due to the abundance of continuously user-generated data sets that could be analyzed and/or published in a privacy-preserving way, and the quick progress made in this research field.

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\section{Summary}
\label{sec:sum-rel}
This is the summary of this chapter.
\kat{? Don't forget to mention here the publication that you have.}
In this chapter, we offer a guide that would allow its users to choose the proper algorithm(s) for their specific use case.
\kat{? Don't forget to mention here the publication that you have.}