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Manos Katsomallos 2021-07-27 09:19:09 +03:00
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text/preliminaries/privacy.tex
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\section{Privacy} \section{Data privacy}
\label{sec:privacy} \label{sec:privacy}
When personal data are publicly released, either as microdata or statistical data, individuals' privacy can be compromised, i.e,~an adversary becomes certain about an individual's personal information with a probability higher than a desired threshold. When personal data are publicly released, either as microdata or statistical data, individuals' privacy can be compromised, i.e,~an adversary becomes certain about an individual's personal information with a probability higher than a desired threshold.
@ -19,7 +19,7 @@ Identity disclosure appears when we can guess that the sixth record of (a privac
Attribute disclosure appears when it is revealed from (a privacy-protected version of) the microdata of Table~\ref{tab:snapshot-micro} that Quackmore is $62$ years old. Attribute disclosure appears when it is revealed from (a privacy-protected version of) the microdata of Table~\ref{tab:snapshot-micro} that Quackmore is $62$ years old.
\subsection{Levels} \subsection{Levels of privacy protection}
\label{subsec:prv-levels} \label{subsec:prv-levels}
The information disclosure that a data release may entail is linked to the protection level that indicates \emph{what} a privacy-preserving algorithm is trying to achieve. The information disclosure that a data release may entail is linked to the protection level that indicates \emph{what} a privacy-preserving algorithm is trying to achieve.
@ -64,7 +64,7 @@ In the extreme cases where $w$ is equal to either $1$ or to the size of the enti
Although the described levels have been coined in the context of \emph{differential privacy}~\cite{dwork2006calibrating}, a seminal privacy method that we will discuss in more detail in Section~\ref{subsec:prv-statistical}, it is possible to apply their definitions to other privacy protection techniques as well. Although the described levels have been coined in the context of \emph{differential privacy}~\cite{dwork2006calibrating}, a seminal privacy method that we will discuss in more detail in Section~\ref{subsec:prv-statistical}, it is possible to apply their definitions to other privacy protection techniques as well.
\subsection{Attacks} \subsection{Attacks to privacy}
\label{subsec:prv-attacks} \label{subsec:prv-attacks}
Information disclosure is typically achieved by combining supplementary (background) knowledge with the released data or by setting unrealistic assumptions while designing the privacy-preserving algorithms. Information disclosure is typically achieved by combining supplementary (background) knowledge with the released data or by setting unrealistic assumptions while designing the privacy-preserving algorithms.
@ -91,7 +91,7 @@ By the data dependence attack, the status of Donald could be more certainly infe
In order to better protect the privacy of Donald in case of attacks, the data should be privacy-protected in a more adequate way (than without the attacks). In order to better protect the privacy of Donald in case of attacks, the data should be privacy-protected in a more adequate way (than without the attacks).
\subsection{Operations} \subsection{Privacy-preserving operations}
\label{subsec:prv-operations} \label{subsec:prv-operations}
Protecting private information, which is known by many names (obfuscation, cloaking, anonymization, etc.), is achieved by using a specific basic privacy protection operation. Protecting private information, which is known by many names (obfuscation, cloaking, anonymization, etc.), is achieved by using a specific basic privacy protection operation.
@ -116,7 +116,7 @@ Our focus is limited to techniques that achieve a satisfying balance between bot
For these reasons, there will be no further discussion around this family of techniques in this article. For these reasons, there will be no further discussion around this family of techniques in this article.
\subsection{Seminal works} \subsection{Seminal works in privacy protection}
\label{subsec:prv-seminal} \label{subsec:prv-seminal}
For completeness, in this section we present the seminal works for privacy-preserving data publishing, which, even though originally designed for the snapshot publishing scenario, have paved the way, since many of the works in privacy-preserving continuous publishing are based on or extend them. For completeness, in this section we present the seminal works for privacy-preserving data publishing, which, even though originally designed for the snapshot publishing scenario, have paved the way, since many of the works in privacy-preserving continuous publishing are based on or extend them.