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b/ACSAC/figures/egd/meps/old_format/meps_egd_utility.pdf diff --git a/ACSAC/figures/fig_advdebias_attacc.tex b/ACSAC/figures/fig_advdebias_attacc.tex new file mode 100644 index 0000000..6c4d29a --- /dev/null +++ b/ACSAC/figures/fig_advdebias_attacc.tex @@ -0,0 +1,139 @@ +% \begin{figure}[!htb] +% \centering +% \begin{minipage}[b]{\linewidth} +% \centering +% \subfigure[\census (\race)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_attack_soft_experimental_race.pdf} +% }% +% \subfigure[\census (\sex)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_attack_soft_experimental_sex.pdf} +% } +% \end{minipage}% + + +% \begin{minipage}[b]{\linewidth} +% \centering +% \subfigure[\compas (\race)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_attack_soft_experimental_race.pdf} +% }% +% \subfigure[\compas (\sex)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_attack_soft_experimental_sex.pdf} +% } +% \end{minipage}% + +% \begin{minipage}[b]{\linewidth} +% \centering +% \subfigure[\meps (\race)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_attack_soft_experimental_race.pdf} +% }% +% \subfigure[\meps (\sex)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_attack_soft_experimental_sex.pdf} +% } +% \end{minipage}% + +% \begin{minipage}[b]{\linewidth} +% \centering +% \subfigure[\lfw (\race)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_attack_soft_experimental_race.pdf} +% }% +% \subfigure[\lfw (\sex)]{ +% \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_attack_soft_experimental_sex.pdf} +% } +% \end{minipage}% + +% \caption{%For both \adaptiveAIASoft and \adaptiveAIAHard, w +% We observe that \advdebias reduces the attack accuracy to random guess ($\sim$50\%). %Additionally for \adaptiveAIAHard, the theoretical bound on attack accuracy (``Theory'') matches with the empirical results (``Empirical''). +% } +% \label{fig:AdaptAIADebias} +% \end{figure} + + + + + +\begin{figure*}[!htb] + \centering + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIASoft: \census (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_attack_soft_experimental_race.pdf} + }% + \subfigure[\adaptiveAIASoft: \census (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_attack_soft_experimental_sex.pdf} + } + \end{minipage}% + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIAHard: \census (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_attack_hard_race.pdf} + }% + \subfigure[\adaptiveAIAHard: \census (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_attack_hard_sex.pdf} + } + \end{minipage}\\ + + + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIASoft: \compas (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_attack_soft_experimental_race.pdf} + }% + \subfigure[\adaptiveAIASoft: \compas (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_attack_soft_experimental_sex.pdf} + } + \end{minipage}% + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIAHard: \compas (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_attack_hard_race.pdf} + }% + \subfigure[\adaptiveAIAHard: \compas (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_attack_hard_sex.pdf} + } + \end{minipage}\\ + + + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIASoft: \meps (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_attack_soft_experimental_race.pdf} + }% + \subfigure[\adaptiveAIASoft: \meps (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_attack_soft_experimental_sex.pdf} + } + \end{minipage}% + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIAHard: \meps (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_attack_hard_race.pdf} + }% + \subfigure[\adaptiveAIAHard: \meps (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_attack_hard_sex.pdf} + } + \end{minipage}\\ + + + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIASoft: \lfw (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_attack_soft_experimental_race.pdf} + }% + \subfigure[\adaptiveAIASoft: \lfw (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_attack_soft_experimental_sex.pdf} + } + \end{minipage}% + \begin{minipage}[b]{0.49\linewidth} + \centering + \subfigure[\adaptiveAIAHard: \lfw (\race)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_attack_hard_race.pdf} + }% + \subfigure[\adaptiveAIAHard: \lfw (\sex)]{ + \includegraphics[width=0.48\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_attack_hard_sex.pdf} + } + \end{minipage} + +\vspace{-2mm} + \caption{For both \adaptiveAIASoft and \adaptiveAIAHard, \advdebias reduces the attack accuracy to random guess ($\sim$50\%). For \adaptiveAIAHard, the theoretical bound on attack accuracy (\theoretical) matches with the empirical results (\empirical).} + \label{fig:AdaptAIADebias} + \vspace{-2mm} +\end{figure*} diff --git a/ACSAC/figures/fig_advdebias_fair.tex b/ACSAC/figures/fig_advdebias_fair.tex new file mode 100644 index 0000000..42e6835 --- /dev/null +++ b/ACSAC/figures/fig_advdebias_fair.tex @@ -0,0 +1,47 @@ + +\begin{figure}[!htb] + \centering + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\census (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_dp_lvl_race.pdf} + }% + \subfigure[\census (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_dp_lvl_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\compas (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_dp_lvl_race.pdf} + }% + \subfigure[\compas (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_dp_lvl_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\meps (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_dp_lvl_race.pdf} + }% + \subfigure[\meps (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_dp_lvl_sex.pdf} + } + \end{minipage}\\ + + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\lfw (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_dp_lvl_race.pdf} + }% + \subfigure[\lfw (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_dp_lvl_sex.pdf} + } + \end{minipage} + + \caption{\dempar-Level for \advdebias: We observe that \dempar-Level is lower for \advdebias indicating $\targetmodel$ is fair.} + \label{fig:DemParAdvDebias2} +\end{figure}
\ No newline at end of file diff --git a/ACSAC/figures/fig_advdebias_utility.tex b/ACSAC/figures/fig_advdebias_utility.tex new file mode 100644 index 0000000..0a87115 --- /dev/null +++ b/ACSAC/figures/fig_advdebias_utility.tex @@ -0,0 +1,23 @@ +\begin{figure}[!htb] + \centering + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\census]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/census/census_advdeb_utility.pdf} + }% + \subfigure[\compas]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/compas/compas_advdeb_utility.pdf} + } + \end{minipage}\\ + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\meps]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/meps/meps_advdeb_utility.pdf} + }% + \subfigure[\lfw]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/advdebias/lfw/lfw_advdeb_utility.pdf} + } + \end{minipage} + \caption{Utility degradation for \advdebias: We observe a statistically significant drop in $\targetmodel$'s accuracy on using \advdebias.} + \label{fig:utilityAdvDebias2} +\end{figure}
\ No newline at end of file diff --git a/ACSAC/figures/fig_egd_attack.tex b/ACSAC/figures/fig_egd_attack.tex new file mode 100644 index 0000000..8b1c713 --- /dev/null +++ b/ACSAC/figures/fig_egd_attack.tex @@ -0,0 +1,50 @@ + +\begin{figure}[!htb] + \centering + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\census (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/census/census_egd_attack_hard_race.pdf} + }% + \subfigure[\census (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/census/census_egd_attack_hard_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\compas (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/compas/compas_egd_attack_hard_race.pdf} + }% + \subfigure[\compas (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/compas/compas_egd_attack_hard_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\meps (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/meps/meps_egd_attack_hard_race.pdf} + }% + \subfigure[\meps (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/meps/meps_egd_attack_hard_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\lfw (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/lfw/lfw_egd_attack_hard_race.pdf} + }% + \subfigure[\lfw (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/lfw/lfw_egd_attack_hard_sex.pdf} + } + \end{minipage} + + \caption{For \adaptiveAIAHard, we observe that \egd reduces the attack accuracy to random guess ($\sim$50\%). %Additionally, the theoretical bound on attack accuracy (``Theory'') matches with the empirical results (``Empirical''). + } + \label{fig:AdaptAIAEGD} +\end{figure} + + +%\textbf{Overall, we observe that using group fairness results in attribute privacy but comes at the cost of $\targetmodel$'s utility.}
\ No newline at end of file diff --git a/ACSAC/figures/fig_egd_fair.tex b/ACSAC/figures/fig_egd_fair.tex new file mode 100644 index 0000000..bed88b8 --- /dev/null +++ b/ACSAC/figures/fig_egd_fair.tex @@ -0,0 +1,46 @@ + +\begin{figure}[!htb] + \centering + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\census (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/census/census_egd_dp_lvl_race.pdf} + }% + \subfigure[\census (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/census/census_egd_dp_lvl_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\compas (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/compas/compas_egd_dp_lvl_race.pdf} + }% + \subfigure[\compas (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/compas/compas_egd_dp_lvl_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\meps (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/meps/meps_egd_dp_lvl_race.pdf} + }% + \subfigure[\meps (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/meps/meps_egd_dp_lvl_sex.pdf} + } + \end{minipage}\\ + + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\lfw (\race)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/lfw/lfw_egd_dp_lvl_race.pdf} + }% + \subfigure[\lfw (\sex)]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/lfw/lfw_egd_dp_lvl_sex.pdf} + } + \end{minipage} + + \caption{\dempar-Level for \egd: We observe that \dempar-Level is lower for \egd than the baseline indicating $\targetmodel$ is fair after \egd.} + \label{fig:DemParegd2} +\end{figure}
\ No newline at end of file diff --git a/ACSAC/figures/fig_egd_utility.tex b/ACSAC/figures/fig_egd_utility.tex new file mode 100644 index 0000000..36ae32a --- /dev/null +++ b/ACSAC/figures/fig_egd_utility.tex @@ -0,0 +1,20 @@ +\begin{figure}[!htb] + \centering + \begin{minipage}[b]{1\linewidth} + \centering + \subfigure[\census]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/census/census_egd_utility.pdf} + }% + \subfigure[\compas]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/compas/compas_egd_utility.pdf} + }\\ + \subfigure[\meps]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/meps/meps_egd_utility.pdf} + }% + \subfigure[\lfw]{ + \includegraphics[width=0.49\linewidth]{ACSAC/figures/egd/lfw/lfw_egd_utility.pdf} + } + \end{minipage} + \caption{Utility degradation for \egd: We observe a statistically significant drop in $\targetmodel$'s accuracy on using \egddp which matches the observation from prior work~\cite{reductions}.} + \label{fig:utilityEGD} +\end{figure}
\ No newline at end of file diff --git a/ACSAC/figures/fig_tm2.tex b/ACSAC/figures/fig_tm2.tex new file mode 100644 index 0000000..9cf489b --- /dev/null +++ b/ACSAC/figures/fig_tm2.tex @@ -0,0 +1,47 @@ +\begin{figure}[t] +\centering +\resizebox{.68\textwidth}{!}{% +\begin{tikzpicture} + + \node [rectangle,draw,thick,minimum width=1.5cm, minimum height=0.75cm] (targetmodel) {$\targetmodel$}; + + \node[below of=targetmodel,yshift=-0.3cm,database,database radius=0.4cm,database segment height=0.2cm, label={below:\footnotesize $\traindata: (X, Y)$}] (trainingdata) {}; + + \node [left of=targetmodel,minimum width=0.75cm,xshift=-0.8cm,fill=red!20,rectangle,draw,thick,label={below:\footnotesize Input}] (inputrecord) {$X'(\omega)$}; + \node [right of=targetmodel,xshift=1.5cm,rectangle,draw,thick] (outputpred) {$\targetmodel(X'(\omega))$}; + % \node [below of=outputpred,minimum width=1.5cm,rectangle,draw,thick] (explanation) {$\phi(x)$}; + + \begin{scope}[on background layer] + \node (tm1) [fit=(targetmodel) (trainingdata), fill= gray!20, rounded corners, inner sep=0.1cm, label={above:\footnotesize }] {}; + \end{scope} + + \node [right of=outputpred,rectangle,draw,thick,minimum width=1.5cm, minimum height=0.75cm,xshift=1.2cm,fill= gray!20] (attmodel) {$\attackmodel$}; + + \node [right of=attmodel,xshift=0.6cm,minimum width=0.75cm,rectangle,draw,thick] (attout) {$S(\omega)$}; + + \node[below of=attmodel,database,database radius=0.4cm,database segment height=0.2cm,yshift=-0.3cm, label={below:\footnotesize $\auxdata: (X', Y', S')$}] (auxdata) {}; + +\begin{scope}[on background layer] + \node (models) [fit=(attmodel) (outputpred) (attout) (auxdata), fill= red!20, rounded corners, inner sep=0.1cm] {}; +\end{scope} + + +\draw[->,ultra thick] (inputrecord.east) -- node[anchor=south, align=center] {\em\footnotesize } (targetmodel.west); +\draw[->,ultra thick] (targetmodel.east) -- node[anchor=south, align=center] {\em\footnotesize } (outputpred.west); +% \draw[->,ultra thick] (targetmodel.east) -- node[anchor=south, align=center] {\em\footnotesize } (explanation.west); + + +\draw[->,ultra thick, dashed] (outputpred.east) -- node[anchor=south, align=center] {\em\footnotesize } (attmodel.west); +% \draw[->,ultra thick, dashed] (explanation.east) -- node[anchor=south, align=center] {\em\footnotesize } (attmodel.west); +\draw[->,ultra thick] (attmodel.east) -- node[anchor=south, align=center] {\em\footnotesize } (attout.west); +\draw[->,ultra thick,dashed] (trainingdata.north) -- node[anchor=south, align=center,label={[yshift=-0.2cm]right:\footnotesize Train}] {\em\footnotesize } (targetmodel.south); +\draw[->,ultra thick,dashed] (auxdata.north) -- node[anchor=south, align=center,label={[yshift=-0.2cm]right:\footnotesize Train}] {\em\footnotesize } (attmodel.south); + + +\end{tikzpicture} +} +\vspace{-1mm} +\caption{\adv wants to infer sensitive attributes for an input given its prediction. \adv trains $\attackmodel$ on $\auxdata$ to map $\targetmodel(X'(\omega))$ to $S'(\omega)$. Once trained, \adv only uses $\targetmodel$'s outputs as input to $\attackmodel$ to infer sensitive attributes. \colorbox{red!20}{red} indicates accessible by \adv.} +\vspace{-1mm} +\label{fig:tm2} +\end{figure}
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version 2.24 (29-Jan-2024) +% Springer Verlag LaTeX2e support for Lecture Notes in Computer Science +% +%% +%% \CharacterTable +%% {Upper-case \A\B\C\D\E\F\G\H\I\J\K\L\M\N\O\P\Q\R\S\T\U\V\W\X\Y\Z +%% Lower-case \a\b\c\d\e\f\g\h\i\j\k\l\m\n\o\p\q\r\s\t\u\v\w\x\y\z +%% Digits \0\1\2\3\4\5\6\7\8\9 +%% Exclamation \! Double quote \" Hash (number) \# +%% Dollar \$ Percent \% Ampersand \& +%% Acute accent \' Left paren \( Right paren \) +%% Asterisk \* Plus \+ Comma \, +%% Minus \- Point \. Solidus \/ +%% Colon \: Semicolon \; Less than \< +%% Equals \= Greater than \> Question mark \? +%% Commercial at \@ Left bracket \[ Backslash \\ +%% Right bracket \] Circumflex \^ Underscore \_ +%% Grave accent \` Left brace \{ Vertical bar \| +%% Right brace \} Tilde \~} +%% +\NeedsTeXFormat{LaTeX2e}[1995/12/01] +\ProvidesClass{llncs}[2024/01/29 v2.24 +^^J LaTeX document class for Lecture Notes in Computer Science] +% Options +\let\if@envcntreset\iffalse +\DeclareOption{envcountreset}{\let\if@envcntreset\iftrue} +\DeclareOption{citeauthoryear}{\let\citeauthoryear=Y} +\DeclareOption{oribibl}{\let\oribibl=Y} +\let\if@custvec\iftrue +\DeclareOption{orivec}{\let\if@custvec\iffalse} +\let\if@envcntsame\iffalse +\DeclareOption{envcountsame}{\let\if@envcntsame\iftrue} +\let\if@envcntsect\iffalse +\DeclareOption{envcountsect}{\let\if@envcntsect\iftrue} +\let\if@runhead\iffalse +\DeclareOption{runningheads}{\let\if@runhead\iftrue} + +\let\if@openright\iftrue +\let\if@openbib\iffalse +\DeclareOption{openbib}{\let\if@openbib\iftrue} + +% languages +\let\switcht@@therlang\relax +\def\ds@deutsch{\def\switcht@@therlang{\switcht@deutsch}} +\def\ds@francais{\def\switcht@@therlang{\switcht@francais}} + +\DeclareOption*{\PassOptionsToClass{\CurrentOption}{article}} + +\ProcessOptions + +\LoadClass[twoside]{article} +\RequirePackage{multicol} % needed for the list of participants, index +\RequirePackage{aliascnt} + +\setlength{\textwidth}{12.2cm} +\setlength{\textheight}{19.3cm} +\renewcommand\@pnumwidth{2em} +\renewcommand\@tocrmarg{3.5em} +% +\def\@dottedtocline#1#2#3#4#5{% + \ifnum #1>\c@tocdepth \else + \vskip \z@ \@plus.2\p@ + {\leftskip #2\relax \rightskip \@tocrmarg \advance\rightskip by 0pt plus 2cm + \parfillskip -\rightskip \pretolerance=10000 + \parindent #2\relax\@afterindenttrue + \interlinepenalty\@M + \leavevmode + \@tempdima #3\relax + \advance\leftskip \@tempdima \null\nobreak\hskip -\leftskip + {#4}\nobreak + \leaders\hbox{$\m@th + \mkern \@dotsep mu\hbox{.}\mkern \@dotsep + mu$}\hfill + \nobreak + \hb@xt@\@pnumwidth{\hfil\normalfont \normalcolor #5}% + \par}% + \fi} +% +\def\switcht@albion{% +\def\abstractname{Abstract.} +\def\ackname{Acknowledgments.} +\def\andname{and} +\def\lastandname{\unskip, and} +\def\appendixname{Appendix} +\def\chaptername{Chapter} +\def\claimname{Claim} +\def\conjecturename{Conjecture} +\def\contentsname{Table of Contents} +\def\corollaryname{Corollary} +\def\definitionname{Definition} +\def\discintname{Disclosure of Interests.} +\def\examplename{Example} +\def\exercisename{Exercise} +\def\figurename{Fig.} +\def\keywordname{{\bf Keywords:}} +\def\indexname{Index} +\def\lemmaname{Lemma} +\def\contriblistname{List of Contributors} +\def\listfigurename{List of Figures} +\def\listtablename{List of Tables} +\def\mailname{{\it Correspondence to\/}:} +\def\noteaddname{Note added in proof} +\def\notename{Note} +\def\partname{Part} +\def\problemname{Problem} +\def\proofname{Proof} +\def\propertyname{Property} +\def\propositionname{Proposition} +\def\questionname{Question} +\def\remarkname{Remark} +\def\seename{see} +\def\solutionname{Solution} +\def\subclassname{{\it Subject Classifications\/}:} +\def\tablename{Table} +\def\theoremname{Theorem}} +\switcht@albion +% Names of theorem like environments are already defined +% but must be translated if another language is chosen +% +% French section +\def\switcht@francais{%\typeout{On parle francais.}% + \def\abstractname{R\'esum\'e.}% + \def\ackname{Remerciements.}% + \def\andname{et}% + \def\lastandname{ et}% + \def\appendixname{Appendice}% + \def\chaptername{Chapitre}% + \def\claimname{Pr\'etention}% + \def\conjecturename{Hypoth\`ese}% + \def\contentsname{Table des mati\`eres}% + \def\corollaryname{Corollaire}% + \def\definitionname{D\'efinition}% + \def\discintname{Mention des Int\'{e}r\^{e}ts.} + \def\examplename{Exemple}% + \def\exercisename{Exercice}% + \def\figurename{Fig.}% + \def\keywordname{{\bf Mots-cl\'e:}}% + \def\indexname{Index}% + \def\lemmaname{Lemme}% + \def\contriblistname{Liste des contributeurs}% + \def\listfigurename{Liste des figures}% + \def\listtablename{Liste des tables}% + \def\mailname{{\it Correspondence to\/}:}% + \def\noteaddname{Note ajout\'ee \`a l'\'epreuve}% + \def\notename{Remarque}% + \def\partname{Partie}% + \def\problemname{Probl\`eme}% + \def\proofname{Preuve}% + \def\propertyname{Caract\'eristique}% +%\def\propositionname{Proposition}% + \def\questionname{Question}% + \def\remarkname{Remarque}% + \def\seename{voir}% + \def\solutionname{Solution}% + \def\subclassname{{\it Subject Classifications\/}:}% + \def\tablename{Tableau}% + \def\theoremname{Th\'eor\`eme}% +} +% +% German section +\def\switcht@deutsch{%\typeout{Man spricht deutsch.}% + \def\abstractname{Zusammenfassung.}% + \def\ackname{Danksagung.}% + \def\andname{und}% + \def\lastandname{ und}% + \def\appendixname{Anhang}% + \def\chaptername{Kapitel}% + \def\claimname{Behauptung}% + \def\conjecturename{Hypothese}% + \def\contentsname{Inhaltsverzeichnis}% + \def\corollaryname{Korollar}% +%\def\definitionname{Definition}% + \def\discintname{Offenlegung von Interessen.} + \def\examplename{Beispiel}% + \def\exercisename{\"Ubung}% + \def\figurename{Abb.}% + \def\keywordname{{\bf Schl\"usselw\"orter:}}% + \def\indexname{Index}% +%\def\lemmaname{Lemma}% + \def\contriblistname{Mitarbeiter}% + \def\listfigurename{Abbildungsverzeichnis}% + \def\listtablename{Tabellenverzeichnis}% + \def\mailname{{\it Correspondence to\/}:}% + \def\noteaddname{Nachtrag}% + \def\notename{Anmerkung}% + \def\partname{Teil}% +%\def\problemname{Problem}% + \def\proofname{Beweis}% + \def\propertyname{Eigenschaft}% +%\def\propositionname{Proposition}% + \def\questionname{Frage}% + \def\remarkname{Anmerkung}% + \def\seename{siehe}% + \def\solutionname{L\"osung}% + \def\subclassname{{\it Subject Classifications\/}:}% + \def\tablename{Tabelle}% +%\def\theoremname{Theorem}% +} + +% Ragged bottom for the actual page +\def\thisbottomragged{\def\@textbottom{\vskip\z@ plus.0001fil +\global\let\@textbottom\relax}} + +\renewcommand\small{% + \@setfontsize\small\@ixpt{11}% + \abovedisplayskip 8.5\p@ \@plus3\p@ \@minus4\p@ + \abovedisplayshortskip \z@ \@plus2\p@ + \belowdisplayshortskip 4\p@ \@plus2\p@ \@minus2\p@ + \def\@listi{\leftmargin\leftmargini + \parsep 0\p@ \@plus1\p@ \@minus\p@ + \topsep 8\p@ \@plus2\p@ \@minus4\p@ + \itemsep0\p@}% + \belowdisplayskip \abovedisplayskip +} + +% Switch to small font size for the credits at the end of the paper +% (i.e. Acknowlegments and Disclosure of Interests) +\newenvironment{credits}{% +\begingroup\small% +\renewcommand\subsubsection{\@startsection{subsubsection}{3}{\z@}% + {-12\p@ \@plus -4\p@ \@minus -4\p@}% + {-0.5em \@plus -0.22em \@minus -0.1em}% + {\normalfont\small\bfseries\boldmath}} +\renewcommand\paragraph{\@startsection{paragraph}{4}{\z@}% + {-8\p@ \@plus -4\p@ \@minus -4\p@}% + {-0.5em \@plus -0.22em \@minus -0.1em}% + {\normalfont\small\itshape}}% +}{\endgroup} + +\frenchspacing +\widowpenalty=10000 +\clubpenalty=10000 + +\setlength\oddsidemargin {63\p@} +\setlength\evensidemargin {63\p@} +\setlength\marginparwidth {90\p@} + +\setlength\headsep {16\p@} + +\setlength\footnotesep{7.7\p@} +\setlength\textfloatsep{8mm\@plus 2\p@ \@minus 4\p@} +\setlength\intextsep {8mm\@plus 2\p@ \@minus 2\p@} + +\setcounter{secnumdepth}{2} + +\newcounter {chapter} +\renewcommand\thechapter {\@arabic\c@chapter} + +\newif\if@mainmatter \@mainmattertrue +\newcommand\frontmatter{\cleardoublepage + \@mainmatterfalse\pagenumbering{Roman}} +\newcommand\mainmatter{\cleardoublepage + \@mainmattertrue\pagenumbering{arabic}} +\newcommand\backmatter{\if@openright\cleardoublepage\else\clearpage\fi + \@mainmatterfalse} + +\renewcommand\part{\cleardoublepage + \thispagestyle{empty}% + \if@twocolumn + \onecolumn + \@tempswatrue + \else + \@tempswafalse + \fi + \null\vfil + \secdef\@part\@spart} + +\def\@part[#1]#2{% + \ifnum \c@secnumdepth >-2\relax + \refstepcounter{part}% + \addcontentsline{toc}{part}{\thepart\hspace{1em}#1}% + \else + \addcontentsline{toc}{part}{#1}% + \fi + \markboth{}{}% + {\centering + \interlinepenalty \@M + \normalfont + \ifnum \c@secnumdepth >-2\relax + \huge\bfseries \partname~\thepart + \par + \vskip 20\p@ + \fi + \Huge \bfseries #2\par}% + \@endpart} +\def\@spart#1{% + {\centering + \interlinepenalty \@M + \normalfont + \Huge \bfseries #1\par}% + \@endpart} +\def\@endpart{\vfil\newpage + \if@twoside + \null + \thispagestyle{empty}% + \newpage + \fi + \if@tempswa + \twocolumn + \fi} + +\newcommand\chapter{\clearpage + \thispagestyle{empty}% + \global\@topnum\z@ + \@afterindentfalse + \secdef\@chapter\@schapter} +\def\@chapter[#1]#2{\ifnum \c@secnumdepth >\m@ne + \if@mainmatter + \refstepcounter{chapter}% + \typeout{\@chapapp\space\thechapter.}% + \addcontentsline{toc}{chapter}% + {\protect\numberline{\thechapter}#1}% + \else + \addcontentsline{toc}{chapter}{#1}% + \fi + \else + \addcontentsline{toc}{chapter}{#1}% + \fi + \chaptermark{#1}% + \addtocontents{lof}{\protect\addvspace{10\p@}}% + \addtocontents{lot}{\protect\addvspace{10\p@}}% + \if@twocolumn + \@topnewpage[\@makechapterhead{#2}]% + \else + \@makechapterhead{#2}% + \@afterheading + \fi} +\def\@makechapterhead#1{% +% \vspace*{50\p@}% + {\centering + \ifnum \c@secnumdepth >\m@ne + \if@mainmatter + \large\bfseries \@chapapp{} \thechapter + \par\nobreak + \vskip 20\p@ + \fi + \fi + \interlinepenalty\@M + \Large \bfseries #1\par\nobreak + \vskip 40\p@ + }} +\def\@schapter#1{\if@twocolumn + \@topnewpage[\@makeschapterhead{#1}]% + \else + \@makeschapterhead{#1}% + \@afterheading + \fi} +\def\@makeschapterhead#1{% +% \vspace*{50\p@}% + {\centering + \normalfont + \interlinepenalty\@M + \Large \bfseries #1\par\nobreak + \vskip 40\p@ + }} + +\renewcommand\section{\@startsection{section}{1}{\z@}% + {-18\p@ \@plus -4\p@ \@minus -4\p@}% + {12\p@ \@plus 4\p@ \@minus 4\p@}% + {\normalfont\large\bfseries\boldmath + \rightskip=\z@ \@plus 8em\pretolerance=10000 }} +\renewcommand\subsection{\@startsection{subsection}{2}{\z@}% + {-18\p@ \@plus -4\p@ \@minus -4\p@}% + {8\p@ \@plus 4\p@ \@minus 4\p@}% + {\normalfont\normalsize\bfseries\boldmath + \rightskip=\z@ \@plus 8em\pretolerance=10000 }} +\renewcommand\subsubsection{\@startsection{subsubsection}{3}{\z@}% + {-18\p@ \@plus -4\p@ \@minus -4\p@}% + {-0.5em \@plus -0.22em \@minus -0.1em}% + {\normalfont\normalsize\bfseries\boldmath}} +\renewcommand\paragraph{\@startsection{paragraph}{4}{\z@}% + {-12\p@ \@plus -4\p@ \@minus -4\p@}% + {-0.5em \@plus -0.22em \@minus -0.1em}% + {\normalfont\normalsize\itshape}} +\renewcommand\subparagraph[1]{\typeout{LLNCS warning: You should not use + \string\subparagraph\space with this class}\vskip0.5cm +You should not use \verb|\subparagraph| with this class.\vskip0.5cm} + +\DeclareMathSymbol{\Gamma}{\mathalpha}{letters}{"00} +\DeclareMathSymbol{\Delta}{\mathalpha}{letters}{"01} +\DeclareMathSymbol{\Theta}{\mathalpha}{letters}{"02} +\DeclareMathSymbol{\Lambda}{\mathalpha}{letters}{"03} +\DeclareMathSymbol{\Xi}{\mathalpha}{letters}{"04} +\DeclareMathSymbol{\Pi}{\mathalpha}{letters}{"05} +\DeclareMathSymbol{\Sigma}{\mathalpha}{letters}{"06} +\DeclareMathSymbol{\Upsilon}{\mathalpha}{letters}{"07} +\DeclareMathSymbol{\Phi}{\mathalpha}{letters}{"08} +\DeclareMathSymbol{\Psi}{\mathalpha}{letters}{"09} +\DeclareMathSymbol{\Omega}{\mathalpha}{letters}{"0A} + +\let\footnotesize\small + +\if@custvec +\DeclareRobustCommand\vec[1]{\mathchoice{\mbox{\boldmath$\displaystyle#1$}} +{\mbox{\boldmath$\textstyle#1$}} +{\mbox{\boldmath$\scriptstyle#1$}} +{\mbox{\boldmath$\scriptscriptstyle#1$}}} +\fi + +\def\squareforqed{\hbox{\rlap{$\sqcap$}$\sqcup$}} +\def\qed{\ifmmode\squareforqed\else{\unskip\nobreak\hfil +\penalty50\hskip1em\null\nobreak\hfil\squareforqed +\parfillskip=0pt\finalhyphendemerits=0\endgraf}\fi} + +\def\getsto{\mathrel{\mathchoice {\vcenter{\offinterlineskip +\halign{\hfil +$\displaystyle##$\hfil\cr\gets\cr\to\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\textstyle##$\hfil\cr\gets +\cr\to\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptstyle##$\hfil\cr\gets +\cr\to\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptscriptstyle##$\hfil\cr +\gets\cr\to\cr}}}}} +\def\lid{\mathrel{\mathchoice {\vcenter{\offinterlineskip\halign{\hfil +$\displaystyle##$\hfil\cr<\cr\noalign{\vskip1.2pt}=\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\textstyle##$\hfil\cr<\cr +\noalign{\vskip1.2pt}=\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptstyle##$\hfil\cr<\cr +\noalign{\vskip1pt}=\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptscriptstyle##$\hfil\cr +<\cr +\noalign{\vskip0.9pt}=\cr}}}}} +\def\gid{\mathrel{\mathchoice {\vcenter{\offinterlineskip\halign{\hfil +$\displaystyle##$\hfil\cr>\cr\noalign{\vskip1.2pt}=\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\textstyle##$\hfil\cr>\cr +\noalign{\vskip1.2pt}=\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptstyle##$\hfil\cr>\cr +\noalign{\vskip1pt}=\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptscriptstyle##$\hfil\cr +>\cr +\noalign{\vskip0.9pt}=\cr}}}}} +\def\grole{\mathrel{\mathchoice {\vcenter{\offinterlineskip +\halign{\hfil +$\displaystyle##$\hfil\cr>\cr\noalign{\vskip-1pt}<\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\textstyle##$\hfil\cr +>\cr\noalign{\vskip-1pt}<\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptstyle##$\hfil\cr +>\cr\noalign{\vskip-0.8pt}<\cr}}} +{\vcenter{\offinterlineskip\halign{\hfil$\scriptscriptstyle##$\hfil\cr +>\cr\noalign{\vskip-0.3pt}<\cr}}}}} +\def\bbbr{{\rm I\!R}} %reelle Zahlen +\def\bbbm{{\rm I\!M}} +\def\bbbn{{\rm I\!N}} %natuerliche Zahlen +\def\bbbf{{\rm I\!F}} +\def\bbbh{{\rm I\!H}} +\def\bbbk{{\rm I\!K}} +\def\bbbp{{\rm I\!P}} +\def\bbbone{{\mathchoice {\rm 1\mskip-4mu l} {\rm 1\mskip-4mu l} +{\rm 1\mskip-4.5mu l} {\rm 1\mskip-5mu l}}} +\def\bbbc{{\mathchoice {\setbox0=\hbox{$\displaystyle\rm C$}\hbox{\hbox +to0pt{\kern0.4\wd0\vrule height0.9\ht0\hss}\box0}} +{\setbox0=\hbox{$\textstyle\rm C$}\hbox{\hbox +to0pt{\kern0.4\wd0\vrule height0.9\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptstyle\rm C$}\hbox{\hbox +to0pt{\kern0.4\wd0\vrule height0.9\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptscriptstyle\rm C$}\hbox{\hbox +to0pt{\kern0.4\wd0\vrule height0.9\ht0\hss}\box0}}}} +\def\bbbq{{\mathchoice {\setbox0=\hbox{$\displaystyle\rm +Q$}\hbox{\raise +0.15\ht0\hbox to0pt{\kern0.4\wd0\vrule height0.8\ht0\hss}\box0}} +{\setbox0=\hbox{$\textstyle\rm Q$}\hbox{\raise +0.15\ht0\hbox to0pt{\kern0.4\wd0\vrule height0.8\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptstyle\rm Q$}\hbox{\raise +0.15\ht0\hbox to0pt{\kern0.4\wd0\vrule height0.7\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptscriptstyle\rm Q$}\hbox{\raise +0.15\ht0\hbox to0pt{\kern0.4\wd0\vrule height0.7\ht0\hss}\box0}}}} +\def\bbbt{{\mathchoice {\setbox0=\hbox{$\displaystyle\rm +T$}\hbox{\hbox to0pt{\kern0.3\wd0\vrule height0.9\ht0\hss}\box0}} +{\setbox0=\hbox{$\textstyle\rm T$}\hbox{\hbox +to0pt{\kern0.3\wd0\vrule height0.9\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptstyle\rm T$}\hbox{\hbox +to0pt{\kern0.3\wd0\vrule height0.9\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptscriptstyle\rm T$}\hbox{\hbox +to0pt{\kern0.3\wd0\vrule height0.9\ht0\hss}\box0}}}} +\def\bbbs{{\mathchoice +{\setbox0=\hbox{$\displaystyle \rm S$}\hbox{\raise0.5\ht0\hbox +to0pt{\kern0.35\wd0\vrule height0.45\ht0\hss}\hbox +to0pt{\kern0.55\wd0\vrule height0.5\ht0\hss}\box0}} +{\setbox0=\hbox{$\textstyle \rm S$}\hbox{\raise0.5\ht0\hbox +to0pt{\kern0.35\wd0\vrule height0.45\ht0\hss}\hbox +to0pt{\kern0.55\wd0\vrule height0.5\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptstyle \rm S$}\hbox{\raise0.5\ht0\hbox +to0pt{\kern0.35\wd0\vrule height0.45\ht0\hss}\raise0.05\ht0\hbox +to0pt{\kern0.5\wd0\vrule height0.45\ht0\hss}\box0}} +{\setbox0=\hbox{$\scriptscriptstyle\rm S$}\hbox{\raise0.5\ht0\hbox +to0pt{\kern0.4\wd0\vrule height0.45\ht0\hss}\raise0.05\ht0\hbox +to0pt{\kern0.55\wd0\vrule height0.45\ht0\hss}\box0}}}} +\def\bbbz{{\mathchoice {\hbox{$\mathsf\textstyle Z\kern-0.4em Z$}} +{\hbox{$\mathsf\textstyle Z\kern-0.4em Z$}} +{\hbox{$\mathsf\scriptstyle Z\kern-0.3em Z$}} +{\hbox{$\mathsf\scriptscriptstyle Z\kern-0.2em Z$}}}} + +\let\ts\, + +\setlength\leftmargini {17\p@} +\setlength\leftmargin {\leftmargini} +\setlength\leftmarginii {\leftmargini} +\setlength\leftmarginiii {\leftmargini} +\setlength\leftmarginiv {\leftmargini} +\setlength \labelsep {.5em} +\setlength \labelwidth{\leftmargini} +\addtolength\labelwidth{-\labelsep} + +\def\@listI{\leftmargin\leftmargini + \parsep 0\p@ \@plus1\p@ \@minus\p@ + \topsep 8\p@ \@plus2\p@ \@minus4\p@ + \itemsep0\p@} +\let\@listi\@listI +\@listi +\def\@listii {\leftmargin\leftmarginii + \labelwidth\leftmarginii + \advance\labelwidth-\labelsep + \topsep 0\p@ \@plus2\p@ \@minus\p@} +\def\@listiii{\leftmargin\leftmarginiii + \labelwidth\leftmarginiii + \advance\labelwidth-\labelsep + \topsep 0\p@ \@plus\p@\@minus\p@ + \parsep \z@ + \partopsep \p@ \@plus\z@ \@minus\p@} + +\renewcommand\labelitemi{\normalfont\bfseries --} +\renewcommand\labelitemii{$\m@th\bullet$} + +\setlength\arraycolsep{1.4\p@} +\setlength\tabcolsep{1.4\p@} + +\def\tableofcontents{\chapter*{\contentsname\@mkboth{{\contentsname}}% + {{\contentsname}}} + \def\authcount##1{\setcounter{auco}{##1}\setcounter{@auth}{1}} + \def\lastand{\ifnum\value{auco}=2\relax + \unskip{} \andname\ + \else + \unskip \lastandname\ + \fi}% + \def\and{\stepcounter{@auth}\relax + \ifnum\value{@auth}=\value{auco}% + \lastand + \else + \unskip, + \fi}% + \@starttoc{toc}\if@restonecol\twocolumn\fi} + +\def\l@part#1#2{\addpenalty{\@secpenalty}% + \addvspace{2em plus\p@}% % space above part line + \begingroup + \parindent \z@ + \rightskip \z@ plus 5em + \hrule\vskip5pt + \large % same size as for a contribution heading + \bfseries\boldmath % set line in boldface + \leavevmode % TeX command to enter horizontal mode. + #1\par + \vskip5pt + \hrule + \vskip1pt + \nobreak % Never break after part entry + \endgroup} + +\def\@dotsep{2} + +\let\phantomsection=\relax + +\def\hyperhrefextend{\ifx\hyper@anchor\@undefined\else +{}\fi} + +\def\addnumcontentsmark#1#2#3{% +\addtocontents{#1}{\protect\contentsline{#2}{\protect\numberline + {\thechapter}#3}{\thepage}\hyperhrefextend}}% +\def\addcontentsmark#1#2#3{% +\addtocontents{#1}{\protect\contentsline{#2}{#3}{\thepage}\hyperhrefextend}}% +\def\addcontentsmarkwop#1#2#3{% +\addtocontents{#1}{\protect\contentsline{#2}{#3}{0}\hyperhrefextend}}% + +\def\@adcmk[#1]{\ifcase #1 \or +\def\@gtempa{\addnumcontentsmark}% + \or \def\@gtempa{\addcontentsmark}% + \or \def\@gtempa{\addcontentsmarkwop}% + \fi\@gtempa{toc}{chapter}% +} +\def\addtocmark{% +\phantomsection +\@ifnextchar[{\@adcmk}{\@adcmk[3]}% +} + +\def\l@chapter#1#2{\addpenalty{-\@highpenalty} + \vskip 1.0em plus 1pt \@tempdima 1.5em \begingroup + \parindent \z@ \rightskip \@tocrmarg + \advance\rightskip by 0pt plus 2cm + \parfillskip -\rightskip \pretolerance=10000 + \leavevmode \advance\leftskip\@tempdima \hskip -\leftskip + {\large\bfseries\boldmath#1}\ifx0#2\hfil\null + \else + \nobreak + \leaders\hbox{$\m@th \mkern \@dotsep mu.\mkern + \@dotsep mu$}\hfill + \nobreak\hbox to\@pnumwidth{\hss #2}% + \fi\par + \penalty\@highpenalty \endgroup} + +\def\l@title#1#2{\addpenalty{-\@highpenalty} + \addvspace{8pt plus 1pt} + \@tempdima \z@ + \begingroup + \parindent \z@ \rightskip \@tocrmarg + \advance\rightskip by 0pt plus 2cm + \parfillskip -\rightskip \pretolerance=10000 + \leavevmode \advance\leftskip\@tempdima \hskip -\leftskip + #1\nobreak + \leaders\hbox{$\m@th \mkern \@dotsep mu.\mkern + \@dotsep mu$}\hfill + \nobreak\hbox to\@pnumwidth{\hss #2}\par + \penalty\@highpenalty \endgroup} + +\def\l@author#1#2{\addpenalty{\@highpenalty} + \@tempdima=15\p@ %\z@ + \begingroup + \parindent \z@ \rightskip \@tocrmarg + \advance\rightskip by 0pt plus 2cm + \pretolerance=10000 + \leavevmode \advance\leftskip\@tempdima %\hskip -\leftskip + \textit{#1}\par + \penalty\@highpenalty \endgroup} + +\setcounter{tocdepth}{0} +\newdimen\tocchpnum +\newdimen\tocsecnum +\newdimen\tocsectotal +\newdimen\tocsubsecnum +\newdimen\tocsubsectotal +\newdimen\tocsubsubsecnum +\newdimen\tocsubsubsectotal +\newdimen\tocparanum +\newdimen\tocparatotal +\newdimen\tocsubparanum +\tocchpnum=\z@ % no chapter numbers +\tocsecnum=15\p@ % section 88. plus 2.222pt +\tocsubsecnum=23\p@ % subsection 88.8 plus 2.222pt +\tocsubsubsecnum=27\p@ % subsubsection 88.8.8 plus 1.444pt +\tocparanum=35\p@ % paragraph 88.8.8.8 plus 1.666pt +\tocsubparanum=43\p@ % subparagraph 88.8.8.8.8 plus 1.888pt +\def\calctocindent{% +\tocsectotal=\tocchpnum +\advance\tocsectotal by\tocsecnum +\tocsubsectotal=\tocsectotal +\advance\tocsubsectotal by\tocsubsecnum +\tocsubsubsectotal=\tocsubsectotal +\advance\tocsubsubsectotal by\tocsubsubsecnum +\tocparatotal=\tocsubsubsectotal +\advance\tocparatotal by\tocparanum} +\calctocindent + +\def\l@section{\@dottedtocline{1}{\tocchpnum}{\tocsecnum}} +\def\l@subsection{\@dottedtocline{2}{\tocsectotal}{\tocsubsecnum}} +\def\l@subsubsection{\@dottedtocline{3}{\tocsubsectotal}{\tocsubsubsecnum}} +\def\l@paragraph{\@dottedtocline{4}{\tocsubsubsectotal}{\tocparanum}} +\def\l@subparagraph{\@dottedtocline{5}{\tocparatotal}{\tocsubparanum}} + +\def\listoffigures{\@restonecolfalse\if@twocolumn\@restonecoltrue\onecolumn + \fi\section*{\listfigurename\@mkboth{{\listfigurename}}{{\listfigurename}}} + \@starttoc{lof}\if@restonecol\twocolumn\fi} +\def\l@figure{\@dottedtocline{1}{0em}{1.5em}} + +\def\listoftables{\@restonecolfalse\if@twocolumn\@restonecoltrue\onecolumn + \fi\section*{\listtablename\@mkboth{{\listtablename}}{{\listtablename}}} + \@starttoc{lot}\if@restonecol\twocolumn\fi} +\let\l@table\l@figure + +\renewcommand\listoffigures{% + \section*{\listfigurename + \@mkboth{\listfigurename}{\listfigurename}}% + \@starttoc{lof}% + } + +\renewcommand\listoftables{% + \section*{\listtablename + \@mkboth{\listtablename}{\listtablename}}% + \@starttoc{lot}% + } + +\ifx\oribibl\undefined +\ifx\citeauthoryear\undefined +\renewenvironment{thebibliography}[1] + {\section*{\refname} + \def\@biblabel##1{##1.} + \small + \list{\@biblabel{\@arabic\c@enumiv}}% + {\settowidth\labelwidth{\@biblabel{#1}}% + \leftmargin\labelwidth + \advance\leftmargin\labelsep + \if@openbib + \advance\leftmargin\bibindent + \itemindent -\bibindent + \listparindent \itemindent + \parsep \z@ + \fi + \usecounter{enumiv}% + \let\p@enumiv\@empty + \renewcommand\theenumiv{\@arabic\c@enumiv}}% + \if@openbib + \renewcommand\newblock{\par}% + \else + \renewcommand\newblock{\hskip .11em \@plus.33em \@minus.07em}% + \fi + \sloppy\clubpenalty4000\widowpenalty4000% + \sfcode`\.=\@m} + {\def\@noitemerr + {\@latex@warning{Empty `thebibliography' environment}}% + \endlist} +\def\@lbibitem[#1]#2{\item[{[#1]}\hfill]\if@filesw + {\let\protect\noexpand\immediate + \write\@auxout{\string\bibcite{#2}{#1}}}\fi\ignorespaces} +\newcount\@tempcntc +\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi + \@tempcnta\z@\@tempcntb\m@ne\def\@citea{}\@cite{\@for\@citeb:=#2\do + {\@ifundefined + {b@\@citeb}{\@citeo\@tempcntb\m@ne\@citea\def\@citea{,}{\bfseries + ?}\@warning + {Citation `\@citeb' on page \thepage \space undefined}}% + {\setbox\z@\hbox{\global\@tempcntc0\csname b@\@citeb\endcsname\relax}% + \ifnum\@tempcntc=\z@ \@citeo\@tempcntb\m@ne + \@citea\def\@citea{,}\hbox{\csname b@\@citeb\endcsname}% + \else + \advance\@tempcntb\@ne + \ifnum\@tempcntb=\@tempcntc + \else\advance\@tempcntb\m@ne\@citeo + \@tempcnta\@tempcntc\@tempcntb\@tempcntc\fi\fi}}\@citeo}{#1}} +\def\@citeo{\ifnum\@tempcnta>\@tempcntb\else + \@citea\def\@citea{,\,\hskip\z@skip}% + \ifnum\@tempcnta=\@tempcntb\the\@tempcnta\else + {\advance\@tempcnta\@ne\ifnum\@tempcnta=\@tempcntb \else + \def\@citea{--}\fi + \advance\@tempcnta\m@ne\the\@tempcnta\@citea\the\@tempcntb}\fi\fi} +\else +\renewenvironment{thebibliography}[1] + {\section*{\refname} + \small + \list{}% + {\settowidth\labelwidth{}% + \leftmargin\parindent + \itemindent=-\parindent + \labelsep=\z@ + \if@openbib + \advance\leftmargin\bibindent + \itemindent -\bibindent + \listparindent \itemindent + \parsep \z@ + \fi + \usecounter{enumiv}% + \let\p@enumiv\@empty + \renewcommand\theenumiv{}}% + \if@openbib + \renewcommand\newblock{\par}% + \else + \renewcommand\newblock{\hskip .11em \@plus.33em \@minus.07em}% + \fi + \sloppy\clubpenalty4000\widowpenalty4000% + \sfcode`\.=\@m} + {\def\@noitemerr + {\@latex@warning{Empty `thebibliography' environment}}% + \endlist} + \def\@cite#1{#1}% + \def\@lbibitem[#1]#2{\item[]\if@filesw + {\def\protect##1{\string ##1\space}\immediate + \write\@auxout{\string\bibcite{#2}{#1}}}\fi\ignorespaces} + \fi +\else +\@cons\@openbib@code{\noexpand\small} +\fi + +\def\idxquad{\hskip 10\p@}% space that divides entry from number + +\def\@idxitem{\par\hangindent 10\p@} + +\def\subitem{\par\setbox0=\hbox{--\enspace}% second order + \noindent\hangindent\wd0\box0}% index entry + +\def\subsubitem{\par\setbox0=\hbox{--\,--\enspace}% third + \noindent\hangindent\wd0\box0}% order index entry + +\def\indexspace{\par \vskip 10\p@ plus5\p@ minus3\p@\relax} + +\renewenvironment{theindex} + {\@mkboth{\indexname}{\indexname}% + \thispagestyle{empty}\parindent\z@ + \parskip\z@ \@plus .3\p@\relax + \let\item\par + \def\,{\relax\ifmmode\mskip\thinmuskip + \else\hskip0.2em\ignorespaces\fi}% + \normalfont\small + \begin{multicols}{2}[\@makeschapterhead{\indexname}]% + } + {\end{multicols}} + +\renewcommand\footnoterule{% + \kern-3\p@ + \hrule\@width 2truecm + \kern2.6\p@} + \newdimen\fnindent + \fnindent1em +\long\def\@makefntext#1{% + \parindent \fnindent% + \leftskip \fnindent% + \noindent + \llap{\hb@xt@1em{\hss\@makefnmark\ }}\ignorespaces#1} + +\long\def\@makecaption#1#2{% + \small + \vskip\abovecaptionskip + \sbox\@tempboxa{{\bfseries #1.} #2}% + \ifdim \wd\@tempboxa >\hsize + {\bfseries #1.} #2\par + \else + \global \@minipagefalse + \hb@xt@\hsize{\hfil\box\@tempboxa\hfil}% + \fi + \vskip\belowcaptionskip} + +\def\fps@figure{htbp} +\def\fnum@figure{\figurename\thinspace\thefigure} +\def \@floatboxreset {% + \reset@font + \small + \@setnobreak + \@setminipage +} +\def\fps@table{htbp} +\def\fnum@table{\tablename~\thetable} +\renewenvironment{table} + {\setlength\abovecaptionskip{0\p@}% + \setlength\belowcaptionskip{10\p@}% + \@float{table}} + {\end@float} +\renewenvironment{table*} + {\setlength\abovecaptionskip{0\p@}% + \setlength\belowcaptionskip{10\p@}% + \@dblfloat{table}} + {\end@dblfloat} + +\long\def\@caption#1[#2]#3{\par\addcontentsline{\csname + ext@#1\endcsname}{#1}{\protect\numberline{\csname + the#1\endcsname}{\ignorespaces #2}}\begingroup + \@parboxrestore + \@makecaption{\csname fnum@#1\endcsname}{\ignorespaces #3}\par + \endgroup} + +% LaTeX does not provide a command to enter the authors institute +% addresses. The \institute command is defined here. + +\newcounter{@inst} +\newcounter{@auth} +\newcounter{auco} +\newdimen\instindent +\newbox\authrun +\newtoks\authorrunning +\newtoks\tocauthor +\newbox\titrun +\newtoks\titlerunning +\newtoks\toctitle + +\def\clearheadinfo{\gdef\@author{No Author Given}% + \gdef\@title{No Title Given}% + \gdef\@subtitle{}% + \gdef\@institute{No Institute Given}% + \gdef\@thanks{}% + \global\titlerunning={}\global\authorrunning={}% + \global\toctitle={}\global\tocauthor={}} + +\def\institute#1{\gdef\@institute{#1}} + +\def\institutename{\par + \begingroup + \parskip=\z@ + \parindent=\z@ + \setcounter{@inst}{1}% + \def\and{\par\stepcounter{@inst}% + \noindent$^{\the@inst}$\enspace\ignorespaces}% + \setbox0=\vbox{\def\thanks##1{}\@institute}% + \ifnum\c@@inst=1\relax + \gdef\fnnstart{0}% + \else + \xdef\fnnstart{\c@@inst}% + \setcounter{@inst}{1}% + \noindent$^{\the@inst}$\enspace + \fi + \ignorespaces + \@institute\par + \endgroup} + +\def\@fnsymbol#1{\ensuremath{\ifcase#1\or\star\or{\star\star}\or + {\star\star\star}\or \dagger\or \ddagger\or + \mathchar "278\or \mathchar "27B\or \|\or **\or \dagger\dagger + \or \ddagger\ddagger \else\@ctrerr\fi}} + +\def\inst#1{\unskip$^{#1}$} +\def\orcidID#1{\unskip$^{[#1]}$} % added MR 2018-03-10 +\def\fnmsep{\unskip$^,$} +\def\email#1{{\tt#1}} + +\AtBeginDocument{\@ifundefined{url}{\def\url#1{#1}}{}% +\@ifpackageloaded{babel}{% +\@ifundefined{extrasenglish}{}{\addto\extrasenglish{\switcht@albion}}% +\@ifundefined{extrasfrenchb}{}{\addto\extrasfrenchb{\switcht@francais}}% +\@ifundefined{extrasgerman}{}{\addto\extrasgerman{\switcht@deutsch}}% +\@ifundefined{extrasngerman}{}{\addto\extrasngerman{\switcht@deutsch}}% +}{\switcht@@therlang}% +\providecommand{\keywords}[1]{\def\and{{\textperiodcentered} }% +\par\addvspace\baselineskip +\noindent\keywordname\enspace\ignorespaces#1}% +\@ifpackageloaded{hyperref}{% +\def\doi#1{\href{https://doi.org/\detokenize{#1}}{\url{https://doi.org/#1}}}}{ +\def\doi#1{https://doi.org/\detokenize{#1}}} +} +\def\homedir{\~{ }} + +\def\subtitle#1{\gdef\@subtitle{#1}} +\clearheadinfo +% +%%% to avoid hyperref warnings +\providecommand*{\toclevel@author}{999} +%%% to make title-entry parent of section-entries +\providecommand*{\toclevel@title}{0} +% +\renewcommand\maketitle{\newpage +\phantomsection + \refstepcounter{chapter}% + \stepcounter{section}% + \setcounter{section}{0}% + \setcounter{subsection}{0}% + \setcounter{figure}{0} + \setcounter{table}{0} + \setcounter{equation}{0} + \setcounter{footnote}{0}% + \begingroup + \parindent=\z@ + \renewcommand\thefootnote{\@fnsymbol\c@footnote}% + \if@twocolumn + \ifnum \col@number=\@ne + \@maketitle + \else + \twocolumn[\@maketitle]% + \fi + \else + \newpage + \global\@topnum\z@ % Prevents figures from going at top of page. + \@maketitle + \fi + \thispagestyle{empty}\@thanks +% + \def\\{\unskip\ \ignorespaces}\def\inst##1{\unskip{}}% + \def\thanks##1{\unskip{}}\def\fnmsep{\unskip}% + \instindent=\hsize + \advance\instindent by-\headlineindent + \if!\the\toctitle!\addcontentsline{toc}{title}{\@title}\else + \addcontentsline{toc}{title}{\the\toctitle}\fi + \if@runhead + \if!\the\titlerunning!\else + \edef\@title{\the\titlerunning}% + \fi + \global\setbox\titrun=\hbox{\small\rm\unboldmath\ignorespaces\@title}% + \ifdim\wd\titrun>\instindent + \typeout{Title too long for running head. Please supply}% + \typeout{a shorter form with \string\titlerunning\space prior to + \string\maketitle}% + \global\setbox\titrun=\hbox{\small\rm + Title Suppressed Due to Excessive Length}% + \fi + \xdef\@title{\copy\titrun}% + \fi +% + \if!\the\tocauthor!\relax + {\def\and{\noexpand\protect\noexpand\and}% + \def\inst##1{}% added MR 2017-09-20 to remove inst numbers from the TOC + \def\orcidID##1{}% added MR 2017-09-20 to remove ORCID ids from the TOC + \protected@xdef\toc@uthor{\@author}}% + \else + \def\\{\noexpand\protect\noexpand\newline}% + \protected@xdef\scratch{\the\tocauthor}% + \protected@xdef\toc@uthor{\scratch}% + \fi + \addtocontents{toc}{\noexpand\protect\noexpand\authcount{\the\c@auco}}% + \addcontentsline{toc}{author}{\toc@uthor}% + \if@runhead + \if!\the\authorrunning! + \value{@inst}=\value{@auth}% + \setcounter{@auth}{1}% + \else + \edef\@author{\the\authorrunning}% + \fi + \global\setbox\authrun=\hbox{\def\inst##1{}% added MR 2017-09-20 to remove inst numbers from the runninghead + \def\orcidID##1{}% added MR 2017-09-20 to remove ORCID ids from the runninghead + \small\unboldmath\@author\unskip}% + \ifdim\wd\authrun>\instindent + \typeout{Names of authors too long for running head. Please supply}% + \typeout{a shorter form with \string\authorrunning\space prior to + \string\maketitle}% + \global\setbox\authrun=\hbox{\small\rm + Authors Suppressed Due to Excessive Length}% + \fi + \xdef\@author{\copy\authrun}% + \markboth{\@author}{\@title}% + \fi + \endgroup + \setcounter{footnote}{\fnnstart}% + \clearheadinfo} +% +\def\@maketitle{\newpage + \markboth{}{}% + \def\lastand{\ifnum\value{@inst}=2\relax + \unskip{} \andname\ + \else + \unskip \lastandname\ + \fi}% + \def\and{\stepcounter{@auth}\relax + \ifnum\value{@auth}=\value{@inst}% + \lastand + \else + \unskip, + \fi}% + \begin{center}% + \let\newline\\ + {\Large \bfseries\boldmath + \pretolerance=10000 + \@title \par}\vskip .8cm +\if!\@subtitle!\else {\large \bfseries\boldmath + \vskip -.65cm + \pretolerance=10000 + \@subtitle \par}\vskip .8cm\fi + \setbox0=\vbox{\setcounter{@auth}{1}\def\and{\stepcounter{@auth}}% + \def\thanks##1{}\@author}% + \global\value{@inst}=\value{@auth}% + \global\value{auco}=\value{@auth}% + \setcounter{@auth}{1}% +{\lineskip .5em +\noindent\ignorespaces +\@author\vskip.35cm} + {\small\institutename} + \end{center}% + } + +% definition of the "\spnewtheorem" command. +% +% Usage: +% +% \spnewtheorem{env_nam}{caption}[within]{cap_font}{body_font} +% or \spnewtheorem{env_nam}[numbered_like]{caption}{cap_font}{body_font} +% or \spnewtheorem*{env_nam}{caption}{cap_font}{body_font} +% +% New is "cap_font" and "body_font". It stands for +% fontdefinition of the caption and the text itself. +% +% "\spnewtheorem*" gives a theorem without number. +% +% A defined spnewthoerem environment is used as described +% by Lamport. +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +\edef\@thmcountersep{} +\edef\@thmcounterend{.} + +\def\spnewtheorem{\@ifstar{\@sthm}{\@Sthm}} + +% definition of \spnewtheorem with number + +\def\@spnthm#1#2{\@ifnextchar[{\@spxnthm{#1}{#2}}{\@spynthm{#1}{#2}}} +\def\@Sthm#1{\@ifnextchar[{\@spothm{#1}}{\@spnthm{#1}}} + +% theorem-like environment with standard counter +\def\@spynthm#1#2#3#4{\expandafter\@ifdefinable\csname #1\endcsname + {\@definecounter{#1}% + \expandafter\xdef\csname the#1\endcsname{\@thmcounter{#1}}% + \expandafter\xdef\csname #1name\endcsname{#2}% + \global\@namedef{#1}{\@spthm{#1}{\csname #1name\endcsname}{#3}{#4}}% + \global\@namedef{end#1}{\@endtheorem}}} + +% theorem-like environment with section-wise counter (envcountsect) +\def\@spxnthm#1#2[#3]#4#5{\expandafter\@ifdefinable\csname #1\endcsname + {\@definecounter{#1}\@addtoreset{#1}{#3}% + \expandafter\xdef\csname the#1\endcsname{\expandafter\noexpand + \csname the#3\endcsname \noexpand\@thmcountersep \@thmcounter{#1}}% + \expandafter\xdef\csname #1name\endcsname{#2}% + \global\@namedef{#1}{\@spthm{#1}{\csname #1name\endcsname}{#4}{#5}}% + \global\@namedef{end#1}{\@endtheorem}}} + +% theorem-like environment with shared counter (envcountsame) +\def\@spothm#1[#2]#3#4#5{% + \@ifundefined{c@#2}{\@latexerr{No theorem environment `#2' defined}\@eha}% + {\expandafter\@ifdefinable\csname #1\endcsname + {\newaliascnt{#1}{#2}% + \expandafter\xdef\csname #1name\endcsname{#3}% + \if@envcntsect + % the following line, introduced in v2.24, fixes incorrect hypertexnames + % when envcountsect is used in combination with envcountsame + \@addtoreset{#1}{section} + \fi + \global\@namedef{#1}{\@spthm{#1}{\csname #1name\endcsname}{#4}{#5}}% + \global\@namedef{end#1}{\@endtheorem}}}} + + + +\def\@spthm#1#2#3#4{\topsep 7\p@ \@plus2\p@ \@minus4\p@ +\refstepcounter{#1}% +\@ifnextchar[{\@spythm{#1}{#2}{#3}{#4}}{\@spxthm{#1}{#2}{#3}{#4}}} + +\def\@spxthm#1#2#3#4{\@spbegintheorem{#2}{\csname the#1\endcsname}{#3}{#4}% + \ignorespaces} + +\def\@spythm#1#2#3#4[#5]{\@spopargbegintheorem{#2}{\csname + the#1\endcsname}{#5}{#3}{#4}\ignorespaces} + +\def\@spbegintheorem#1#2#3#4{\trivlist + \item[\hskip\labelsep{#3#1\ #2\@thmcounterend}]#4} + +\def\@spopargbegintheorem#1#2#3#4#5{\trivlist + \item[\hskip\labelsep{#4#1\ #2}]{#4(#3)\@thmcounterend\ }#5} + +% definition of \spnewtheorem* without number + +\def\@sthm#1#2{\@Ynthm{#1}{#2}} + +\def\@Ynthm#1#2#3#4{\expandafter\@ifdefinable\csname #1\endcsname + {\global\@namedef{#1}{\@Thm{\csname #1name\endcsname}{#3}{#4}}% + \expandafter\xdef\csname #1name\endcsname{#2}% + \global\@namedef{end#1}{\@endtheorem}}} + +\def\@Thm#1#2#3{\topsep 7\p@ \@plus2\p@ \@minus4\p@ +\@ifnextchar[{\@Ythm{#1}{#2}{#3}}{\@Xthm{#1}{#2}{#3}}} + +\def\@Xthm#1#2#3{\@Begintheorem{#1}{#2}{#3}\ignorespaces} + +\def\@Ythm#1#2#3[#4]{\@Opargbegintheorem{#1} + {#4}{#2}{#3}\ignorespaces} + +\def\@Begintheorem#1#2#3{#3\trivlist + \item[\hskip\labelsep{#2#1\@thmcounterend}]} + +\def\@Opargbegintheorem#1#2#3#4{#4\trivlist + \item[\hskip\labelsep{#3#1}]{#3(#2)\@thmcounterend\ }} + +\if@envcntsect + \def\@thmcountersep{.} + \spnewtheorem{theorem}{Theorem}[section]{\bfseries}{\itshape} +\else + \spnewtheorem{theorem}{Theorem}{\bfseries}{\itshape} + \if@envcntreset + \@addtoreset{theorem}{section} + \else + \@addtoreset{theorem}{chapter} + \fi +\fi + +%definition of various theorem environments +\spnewtheorem*{claim}{Claim}{\itshape}{\rmfamily} +\spnewtheorem*{proof}{Proof}{\itshape}{\rmfamily} +\if@envcntsame % alle Umgebungen wie Theorem. + \def\spn@wtheorem#1#2#3#4{\@spothm{#1}[theorem]{#2}{#3}{#4}} +\else % alle Umgebungen mit eigenem Zaehler + \if@envcntsect % mit section numeriert + \def\spn@wtheorem#1#2#3#4{\@spxnthm{#1}{#2}[section]{#3}{#4}} + \else % nicht mit section numeriert + \if@envcntreset + \def\spn@wtheorem#1#2#3#4{\@spynthm{#1}{#2}{#3}{#4} + \@addtoreset{#1}{section}} + \else + \def\spn@wtheorem#1#2#3#4{\@spynthm{#1}{#2}{#3}{#4} + \@addtoreset{#1}{chapter}}% + \fi + \fi +\fi +\spn@wtheorem{case}{Case}{\itshape}{\rmfamily} +\spn@wtheorem{conjecture}{Conjecture}{\itshape}{\rmfamily} +\spn@wtheorem{corollary}{Corollary}{\bfseries}{\itshape} +\spn@wtheorem{definition}{Definition}{\bfseries}{\itshape} +\spn@wtheorem{example}{Example}{\itshape}{\rmfamily} +\spn@wtheorem{exercise}{Exercise}{\itshape}{\rmfamily} +\spn@wtheorem{lemma}{Lemma}{\bfseries}{\itshape} +\spn@wtheorem{note}{Note}{\itshape}{\rmfamily} +\spn@wtheorem{problem}{Problem}{\itshape}{\rmfamily} +\spn@wtheorem{property}{Property}{\itshape}{\rmfamily} +\spn@wtheorem{proposition}{Proposition}{\bfseries}{\itshape} +\spn@wtheorem{question}{Question}{\itshape}{\rmfamily} +\spn@wtheorem{solution}{Solution}{\itshape}{\rmfamily} +\spn@wtheorem{remark}{Remark}{\itshape}{\rmfamily} + +\def\@takefromreset#1#2{% + \def\@tempa{#1}% + \let\@tempd\@elt + \def\@elt##1{% + \def\@tempb{##1}% + \ifx\@tempa\@tempb\else + \@addtoreset{##1}{#2}% + \fi}% + \expandafter\expandafter\let\expandafter\@tempc\csname cl@#2\endcsname + \expandafter\def\csname cl@#2\endcsname{}% + \@tempc + \let\@elt\@tempd} + +\def\theopargself{\def\@spopargbegintheorem##1##2##3##4##5{\trivlist + \item[\hskip\labelsep{##4##1\ ##2}]{##4##3\@thmcounterend\ }##5} + \def\@Opargbegintheorem##1##2##3##4{##4\trivlist + \item[\hskip\labelsep{##3##1}]{##3##2\@thmcounterend\ }} + } + +\renewenvironment{abstract}{% + \list{}{\advance\topsep by0.35cm\relax\small + \leftmargin=1cm + \labelwidth=\z@ + \listparindent=\z@ + \itemindent\listparindent + \rightmargin\leftmargin}\item[\hskip\labelsep + \bfseries\abstractname]} + {\endlist} + +\newdimen\headlineindent % dimension for space between +\headlineindent=1.166cm % number and text of headings. + +\def\ps@headings{\let\@mkboth\@gobbletwo + \let\@oddfoot\@empty\let\@evenfoot\@empty + \def\@evenhead{\normalfont\small\rlap{\thepage}\hspace{\headlineindent}% + \leftmark\hfil} + \def\@oddhead{\normalfont\small\hfil\rightmark\hspace{\headlineindent}% + \llap{\thepage}} + \def\chaptermark##1{}% + \def\sectionmark##1{}% + \def\subsectionmark##1{}} + +\def\ps@titlepage{\let\@mkboth\@gobbletwo + \let\@oddfoot\@empty\let\@evenfoot\@empty + \def\@evenhead{\normalfont\small\rlap{\thepage}\hspace{\headlineindent}% + \hfil} + \def\@oddhead{\normalfont\small\hfil\hspace{\headlineindent}% + \llap{\thepage}} + \def\chaptermark##1{}% + \def\sectionmark##1{}% + \def\subsectionmark##1{}} + +\if@runhead\ps@headings\else +\ps@empty\fi + +\setlength\arraycolsep{1.4\p@} +\setlength\tabcolsep{1.4\p@} + +\endinput +%end of file llncs.cls diff --git a/ACSAC/paper.bib b/ACSAC/paper.bib new file mode 100644 index 0000000..ec7377e --- /dev/null +++ b/ACSAC/paper.bib @@ -0,0 +1,1204 @@ +@misc{carlini2022membership, + title={Membership Inference Attacks From First Principles}, + author={Nicholas Carlini and Steve Chien and Milad Nasr and Shuang Song and Andreas Terzis and Florian Tramer}, + year={2022}, + eprint={2112.03570}, + archivePrefix={arXiv}, + primaryClass={cs.CR} +} + +@inproceedings{salem2023sok, + title={SoK: Let the privacy games begin! A unified treatment of data inference privacy in machine learning}, + author={Salem, Ahmed and Cherubin, Giovanni and Evans, David and K{\"o}pf, Boris and Paverd, Andrew and Suri, Anshuman and Tople, Shruti and Zanella-B{\'e}guelin, Santiago}, + booktitle={2023 IEEE Symposium on Security and Privacy (SP)}, + pages={327--345}, + year={2023}, + organization={IEEE} +} + + +@inproceedings{ijcai2022p766, + title = {Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey}, + author = {Fioretto, Ferdinando and Tran, Cuong and Van Hentenryck, Pascal and Zhu, Keyu}, + booktitle = {Proceedings of the Thirty-First International Joint Conference on + Artificial Intelligence, {IJCAI-22}}, + publisher = {International Joint Conferences on Artificial Intelligence Organization}, + editor = {Lud De Raedt}, + pages = {5470--5477}, + year = {2022}, + month = {7}, + note = {Survey Track}, + doi = {10.24963/ijcai.2022/766}, + url = {https://doi.org/10.24963/ijcai.2022/766}, +} + +@article{accfairtradeoff, +author = {Pinzon, Carlos and Palamidessi, Catuscia and Piantanida, Pablo and Valencia, Frank}, +year = {2023}, +month = {05}, +pages = {1-30}, +title = {On the incompatibility of accuracy and equal opportunity}, +journal = {Machine Learning}, +doi = {10.1007/s10994-023-06331-y} +} + +@article{rodolfa2021empirical, + title={Empirical observation of negligible fairness--accuracy trade-offs in machine learning for public policy}, + author={Rodolfa, Kit T and Lamba, Hemank and Ghani, Rayid}, + journal={Nature Machine Intelligence}, + volume={3}, + number={10}, + pages={896--904}, + year={2021}, + publisher={Nature Publishing Group UK London} +} + +@article{zhai2022understanding, + title={Understanding why generalized reweighting does not improve over ERM}, + author={Zhai, Runtian and Dan, Chen and Kolter, Zico and Ravikumar, Pradeep}, + booktitle={International Conference on Learning Representation}, + year={2023} +} + +@article{ +veldanda2022fairness, +title={Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale with MinDiff Loss}, +author={Akshaj Kumar Veldanda and Ivan Brugere and Jiahao Chen and Sanghamitra Dutta and Alan Mishler and Siddharth Garg}, +journal={Transactions on Machine Learning Research}, +issn={2835-8856}, +year={2023}, +url={https://openreview.net/forum?id=f4VyYhkRvi}, +note={} +} + +% general +% url = {https://arxiv.org/abs/2206.10923}, +@misc{arxivmichael, + doi = {10.48550/ARXIV.2206.10923}, + author = {Maheshwari, Gaurav and Perrot, Michaël}, + title = {FairGrad: Fairness Aware Gradient Descent}, + publisher = {arXiv}, + year = {2022}, +} + + +@InProceedings{classIMb1, + title = {Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding}, + author = {Guo, Lan-Zhe and Li, Yu-Feng}, + booktitle = {Proceedings of the 39th International Conference on Machine Learning}, + pages = {8082--8094}, + year = {2022}, + editor = {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and Szepesvari, Csaba and Niu, Gang and Sabato, Sivan}, + volume = {162}, + series = {Proceedings of Machine Learning Research}, + month = {17--23 Jul}, + publisher = {PMLR}, + pdf = {https://proceedings.mlr.press/v162/guo22e/guo22e.pdf}, + url = {https://proceedings.mlr.press/v162/guo22e.html} +} + +@article{classIMb2, + title={Deep learning model calibration for improving performance in class-imbalanced medical image classification tasks}, + author={Sivaramakrishnan Rajaraman and Prasanth Ganesan and Sameer K. Antani}, + journal={PLoS ONE}, + year={2021}, + volume={17}, + url={https://api.semanticscholar.org/CorpusID:238259577} +} + +@misc{classIMb3, + author = {Jason Brownlee}, + title = {{A} {G}entle {I}ntroduction to {T}hreshold-{M}oving for {I}mbalanced {C}lassification - {M}achine{L}earning{M}astery.com --- machinelearningmastery.com}, + year = {}, + note = {[Accessed 31-08-2023]}, +} +%issn = {0022-0000}, +%url = {https://www.sciencedirect.com/science/article/pii/S002200009791504X}, +@article{saddlepointsolve, +title = {A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting}, +journal = {Journal of Computer and System Sciences}, +volume = {55}, +number = {1}, +pages = {119-139}, +year = {1997}, +doi = {10.1006/jcss.1997.1504}, +author = {Yoav Freund and Robert E Schapire} +} + + + +%isbn = {1595933832}, +%address = {New York, NY, USA}, +@inproceedings{curves, +author = {Davis, Jesse and Goadrich, Mark}, +title = {The Relationship between Precision-Recall and ROC Curves}, +year = {2006}, +publisher = {Association for Computing Machinery}, +doi = {10.1145/1143844.1143874}, +booktitle = {International Conference on Machine Learning}, +pages = {233–240}, +location = {Pittsburgh, Pennsylvania, USA}, +series = {ICML '06} +} + + +@inproceedings{cormode, +author = {Cormode, Graham}, +title = {Personal Privacy vs Population Privacy: Learning to Attack Anonymization}, +year = {2011}, +publisher = {Association for Computing Machinery}, +doi = {10.1145/2020408.2020598}, +booktitle = {ACM SIGKDD International Conference on Knowledge Discovery and Data Mining}, +pages = {1253–1261}, +location = {San Diego, California, USA}, +series = {KDD '11} +} + +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%issn = {0360-0300}, +%url = {https://doi.org/10.1145/3457607}, +@article{surveyfair, +author = {Mehrabi, Ninareh and Morstatter, Fred and Saxena, Nripsuta and Lerman, Kristina and Galstyan, Aram}, +title = {A Survey on Bias and Fairness in Machine Learning}, +year = {2021}, +volume = {54}, +number = {6}, +doi = {10.1145/3457607}, +journal = {ACM Comput. Surv.}, +month = {jul}, +articleno = {115}, +numpages = {35}, +} + + +@article{attinfSocial1, +author = {Gong, Neil Zhenqiang and Talwalkar, Ameet and Mackey, Lester and Huang, Ling and Shin, Eui Chul Richard and Stefanov, Emil and Shi, Elaine (Runting) and Song, Dawn}, +title = {Joint Link Prediction and Attribute Inference Using a Social-Attribute Network}, +year = {2014}, +publisher = {Association for Computing Machinery}, +volume = {5}, +number = {2}, +doi = {10.1145/2594455}, +journal = {ACM Trans. Intell. Syst. Technol.}, +} + + +%address = {New York, NY, USA}, + +%issn = {2471-2566}, +%url = {https://doi.org/10.1145/3154793}, +%numpages = {30}, +%%month = {jan}, +@article{attinfSocial2, +author = {Gong, Neil Zhenqiang and Liu, Bin}, +title = {Attribute Inference Attacks in Online Social Networks}, +year = {2018}, +publisher = {Association for Computing Machinery}, +volume = {21}, +number = {1}, +doi = {10.1145/3154793}, +journal = {ACM Trans. Priv. Secur.}, +articleno = {3}, +} + +%isbn = {978-1-931971-32-4}, +%address = {Austin, TX}, +%url = {https://www.usenix.org/conference/usenixsecurity16/technical-sessions/presentation/gong}, +%publisher = {USENIX Association}, +%month = aug, +@inproceedings {attinfSocial3, +author = {Neil Zhenqiang Gong and Bin Liu}, +title = {You Are Who You Know and How You Behave: Attribute Inference Attacks via Users{\textquoteright} Social Friends and Behaviors}, +booktitle = {USENIX Security Symposium }, +year = {2016}, +pages = {979--995}, +} + + + %URL = {https://hal.inria.fr/hal-00748162}, + %ADDRESS = {San Diego, United States}, + %MONTH = Feb, +@inproceedings{attinfSocial4, + TITLE = {{You Are What You Like! Information Leakage Through Users' Interests}}, + YEAR = {2012}, + AUTHOR = {Chaabane, Abdelberi and Acs, Gergely and Kaafar, Mohamed Ali}, + BOOKTITLE = {Network and Distributed System Security Symposium}, + PAGES = {1-14}, +} + + + + +@inproceedings{attinfSocial5, + author={Elena Zheleva and Lise Getoor}, + title={To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles}, + year={2009}, + BOOKTITLE = {International Conference on World Wide Web}, + pages={531-540}, + doi={10.1145/1526709.1526781}, +} + + + +%isbn = {9781450349130}, +%publisher = {International World Wide Web Conferences Steering Committee}, +%address = {Republic and Canton of Geneva, CHE}, +%url = {https://doi.org/10.1145/3038912.3052695}, +@inproceedings{attinfSocial6, +author = {Jia, Jinyuan and Wang, Binghui and Zhang, Le and Gong, Neil Zhenqiang}, +title = {AttriInfer: Inferring User Attributes in Online Social Networks Using Markov Random Fields}, +year = {2017}, +doi = {10.1145/3038912.3052695}, +booktitle = {nternational Conference on World Wide Web}, +pages = {1561–1569}, +location = {Perth, Australia}, +series = {WWW '17} +} + + + +%isbn = {9781450382878}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +@inbook{dysan, +author = {Boutet, Antoine and Frindel, Carole and Gambs, S\'{e}bastien and Jourdan, Th\'{e}o and Ngueveu, Rosin Claude}, +title = {DySan: Dynamically Sanitizing Motion Sensor Data Against Sensitive Inferences through Adversarial Networks}, +year = {2021}, +doi = {10.1145/3433210.3453095}, +booktitle = {ACM Asia Conference on Computer and Communications Security}, +pages = {672–686}, +serie = {ASIA CCS '21} +} + +@inproceedings{attprivacy, +author = {Zhang, Wanrong and Ohrimenko, Olga and Cummings, Rachel}, +title = {Attribute Privacy: Framework and Mechanisms}, +year = {2022}, +isbn = {9781450393522}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +url = {https://doi.org/10.1145/3531146.3533139}, +doi = {10.1145/3531146.3533139}, +booktitle = {Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency}, +pages = {757–766}, +numpages = {10}, +keywords = {Pufferfish privacy, attribute privacy, formal privacy frameworks, privacy-preserving mechanisms}, +series = {FAccT '22} +} + +%differential privacy and fairness +@inproceedings{dispvuln, +author = {Mohammad Yaghini and Bogdan Kulynych and Carmela Troncoso}, +title = {Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning}, +year = {2022}, +booktitle = {Privacy Enhancing Technologies Symposium} +} + + +%isbn = {9781450391405}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +@inproceedings{GongMIAUnfair, +author = {Zhong, Da and Sun, Haipei and Xu, Jun and Gong, Neil and Wang, Wendy Hui}, +title = {Understanding Disparate Effects of Membership Inference Attacks and Their Countermeasures}, +year = {2022}, +doi = {10.1145/3488932.3501279}, +booktitle = {ACM on Asia Conference on Computer and Communications Security}, +pages = {959–974}, +location = {Nagasaki, Japan}, +series = {ASIA CCS '22} +} + + +%sbn = {9781450311151}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%url = {https://doi.org/10.1145/2090236.2090255}, +@inproceedings{indivfairness, +author = {Dwork, Cynthia and Hardt, Moritz and Pitassi, Toniann and Reingold, Omer and Zemel, Richard}, +title = {Fairness through Awareness}, +year = {2012}, +doi = {10.1145/2090236.2090255}, +booktitle = {Innovations in Theoretical Computer Science Conference}, +pages = {214–226}, +location = {Cambridge, Massachusetts}, +series = {ITCS '12} +} + +@inproceedings{outIndist, +author = {Dwork, Cynthia and Kim, Michael P. and Reingold, Omer and Rothblum, Guy N. and Yona, Gal}, +title = {Outcome indistinguishability}, +year = {2021}, +isbn = {9781450380539}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +url = {https://doi.org/10.1145/3406325.3451064}, +doi = {10.1145/3406325.3451064}, +booktitle = {Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing}, +pages = {1095–1108}, +numpages = {14}, +keywords = {Prediction, Fairness, Computational Indistinguishability}, +location = {Virtual, Italy}, +series = {STOC 2021} +} + + + + + +%isbn = {9781450369367}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%url = {https://doi.org/10.1145/3351095.3372872}, +@inproceedings{dpfair, +author = {Pujol, David and McKenna, Ryan and Kuppam, Satya and Hay, Michael and Machanavajjhala, Ashwin and Miklau, Gerome}, +title = {Fair Decision Making Using Privacy-Protected Data}, +year = {2020}, +doi = {10.1145/3351095.3372872}, +booktitle = {Conference on Fairness, Accountability, and Transparency}, +pages = {189–199}, +location = {Barcelona, Spain}, +series = {FAT* '20} +} + +%url={https://ojs.aaai.org/index.php/AAAI/article/view/17193}, +%month={May}, +@article{fairprivatelagrangian, +title={Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach}, +volume={35}, +number={11}, +journal={AAAI Conference on Artificial Intelligence}, +author={Tran, Cuong and Fioretto, Ferdinando and Van Hentenryck, Pascal}, +year={2021}, +pages={9932-9939} +} + +%editor = {Chaudhuri, Kamalika and Salakhutdinov, Ruslan}, + %series = {Proceedings of Machine Learning Research}, + %month = {09--15 Jun}, + %publisher = {PMLR}, + %pdf = {http://proceedings.mlr.press/v97/jagielski19a/jagielski19a.pdf}, + %url = {https://proceedings.mlr.press/v97/jagielski19a.html} +@InProceedings{dpfairlearn, + title = {Differentially Private Fair Learning}, + author = {Jagielski, Matthew and Kearns, Michael and Mao, Jieming and Oprea, Alina and Roth, Aaron and -Malvajerdi, Saeed Sharifi and Ullman, Jonathan}, + booktitle = {International Conference on Machine Learning}, + pages = {3000--3008}, + year = {2019}, + volume = {97}, +} + +@incollection{dpaccdisp, +title = {Differential Privacy Has Disparate Impact on Model Accuracy}, +author = {Bagdasaryan, Eugene and Poursaeed, Omid and Shmatikov, Vitaly}, +booktitle = {Advances in Neural Information Processing Systems}, +pages = {15479--15488}, +year = {2019}} + +%isbn = {978-1-939133-06-9}, +%address = {Santa Clara, CA}, +%url = {https://www.usenix.org/conference/usenixsecurity19/presentation/jayaraman}, +%publisher = {USENIX Association}, +%month = aug, +@inproceedings {dpVacc, +author = {Bargav Jayaraman and David Evans}, +title = {Evaluating Differentially Private Machine Learning in Practice}, +booktitle = {USENIX Security Symposium}, +year = {2019}, +pages = {1895--1912}, +} + +%isbn = {9781450367110}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%url = {https://doi.org/10.1145/3314183.3323847}, +@inproceedings{cummings, +author = {Cummings, Rachel and Gupta, Varun and Kimpara, Dhamma and Morgenstern, Jamie}, +title = {On the Compatibility of Privacy and Fairness}, +year = {2019}, +doi = {10.1145/3314183.3323847}, +booktitle = {Conference on User Modeling, Adaptation and Personalization}, +pages = {309–315}, +location = {Larnaca, Cyprus}, +series = {UMAP'19 Adjunct} +} + + +@techreport{ec2019ethics, + address = {Brussels}, + author = {{High-Level Expert Group on AI}}, + institution = {European Commission}, + language = {eng}, + month = apr, + title = {Ethics guidelines for trustworthy AI}, + type = {Report}, + url = {https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai}, + year = {2019} +} + +@inproceedings{nist, + title={A Taxonomy and Terminology of Adversarial Machine Learning}, + author={Elham Tabassi and Kevin J. Burns and M. Hadjimichael and Andres Molina-Markham and Julian Sexton}, + url = {https://nvlpubs.nist.gov/nistpubs/ir/2019/NIST.IR.8269-draft.pdf}, + year={2019}, + booktitle = {NIST Interagency/Internal Report} +} + +@inproceedings{dpia, +title={Art. 35 {GDPR} Data protection impact assessment}, +url={https://gdpr-info.eu/art-35-gdpr/}, +author={European Union Law}, +year={2018}, +booktitle={General Data Protection Regulation (GDPR)} } + +@article{ico, +title={{AI} auditing and impact assessment: according to the UK information commissioner’s office}, ISSN={2730-5953, 2730-5961}, url={http://link.springer.com/10.1007/s43681-021-00039-2}, DOI={10.1007/s43681-021-00039-2}, +journal={AI and Ethics}, +author={Kazim, Emre and Denny, Danielle Mendes Thame and Koshiyama, Adriano}, +year={2021}, +month={Feb} } + +@inproceedings{whitehouse, +title={Guidance for Regulation of Artificial Intelligence Applications}, +url={https://www.whitehouse.gov/wp-content/uploads/2020/11/M-21-06.pdf}, +author={White House}, +year = {2020}, +booktitle={Memorandum For The Heads Of Executive Departments And Agencies} } + +%metrics + +@INPROCEEDINGS{memprivNattpriv, + author={Zhao, Benjamin Zi Hao and Agrawal, Aviral and Coburn, Catisha and Asghar, Hassan Jameel and Bhaskar, Raghav and Kaafar, Mohamed Ali and Webb, Darren and Dickinson, Peter}, + booktitle={IEEE European Symposium on Security and Privacy}, + title={On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models}, + year={2021}, + pages={232-251}, + doi={10.1109/EuroSP51992.2021.00025} +} + +@article{duddu2023sok, + title={SoK: Unintended Interactions among Machine Learning Defenses and Risks}, + author={Duddu, Vasisht and Szyller, Sebastian and Asokan, N}, + journal={arXiv preprint arXiv:2312.04542}, + year={2023} +} + + +@inproceedings{suri2023dissecting, + title={Dissecting distribution inference}, + author={Suri, Anshuman and Lu, Yifu and Chen, Yanjin and Evans, David}, + booktitle={2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)}, + pages={150--164}, + year={2023}, + organization={IEEE} +} + + +@article{de2020overview, + title={An overview of privacy in machine learning}, + author={De Cristofaro, Emiliano}, + journal={arXiv preprint arXiv:2005.08679}, + year={2020} +} + + +@article{pate2021fairness, + title={A Fairness Analysis on Private Aggregation of Teacher Ensembles}, + author={Tran, Cuong and Dinh, My H and Beiter, Kyle and Fioretto, Ferdinando}, + journal={arXiv preprint arXiv:2109.08630}, + year={2021} +} + +@article{fioretto2022differential, + title={Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey}, + author={Fioretto, Ferdinando and Tran, Cuong and Van Hentenryck, Pascal and Zhu, Keyu}, + journal={arXiv preprint arXiv:2202.08187}, + year={2022} +} + + +% attribute inference attacks in ML +%publisher = "Institute of Electrical and Electronics Engineers (IEEE)", +%address = "United States", +@inproceedings{zhao2021infeasibility, +title = "On the (in)feasibility of attribute inference attacks on machine learning models", +author = "Zhao, {Benjamin Zi Hao} and Aviral Agrawal and Catisha Coburn and Asghar, {Hassan Jameel} and Raghav Bhaskar and Kaafar, {Mohamed Ali} and Darren Webb and Peter Dickinson", +year = "2021", +doi = "10.1109/EuroSP51992.2021.00025", +pages = "232--251", +booktitle = "IEEE European Symposium on Security and Privacy", +serie = {EuroS&P '2021}, +} + + +%isbn = {978-1-939133-31-1}, +%address = {Boston, MA}, +%url = {https://www.usenix.org/conference/usenixsecurity22/presentation/mehnaz}, +%publisher = {USENIX Association}, +%month = aug, +@inproceedings{MehnazAttInf, +author = {Shagufta Mehnaz and Sayanton V. Dibbo and Ehsanul Kabir and Ninghui Li and Elisa Bertino}, +title = {Are Your Sensitive Attributes Private? Novel Model Inversion Attribute Inference Attacks on Classification Models}, +booktitle = {USENIX Security Symposium}, +year = {2022}, +pages = {4579--4596}, +} + +%isbn = {9781450338325}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%%url = {https://doi.org/10.1145/2810103.2813677}, +@inproceedings{fredrikson1, +author = {Fredrikson, Matt and Jha, Somesh and Ristenpart, Thomas}, +title = {Model Inversion Attacks That Exploit Confidence Information and Basic Countermeasures}, +year = {2015}, +doi = {10.1145/2810103.2813677}, +booktitle = {ACM SIGSAC Conference on Computer and Communications Security}, +pages = {1322–1333}, +location = {Denver, Colorado, USA}, +series = {CCS '15} +} + + +%isbn = {9781931971157}, +@inproceedings{fredrikson2, +author = {Fredrikson, Matthew and Lantz, Eric and Jha, Somesh and Lin, Simon and Page, David and Ristenpart, Thomas}, +title = {Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing}, +year = {2014}, +booktitle = {USENIX Conference on Security Symposium}, +pages = {17–32}, +location = {San Diego, CA}, +series = {SEC'14} +} + +@inproceedings{Song2020Overlearning, +title={Overlearning Reveals Sensitive Attributes}, +author={Congzheng Song and Vitaly Shmatikov}, +booktitle={International Conference on Learning Representations}, +year={2020} +} + + +%isbn = {9781450384544}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%url = {https://doi.org/10.1145/3460120.3484533}, +@inproceedings{malekzadeh2021honestbutcurious, +author = {Malekzadeh, Mohammad and Borovykh, Anastasia and G\"{u}nd\"{u}z, Deniz}, +title = {Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs}, +year = {2021}, +doi = {10.1145/3460120.3484533}, +booktitle = {ACM SIGSAC Conference on Computer and Communications Security}, +pages = {825–844}, +location = {Virtual Event, Republic of Korea}, +series = {CCS '21} +} + + +@article{jayaraman2022attribute, + title={Are Attribute Inference Attacks Just Imputation?}, + author={Jayaraman, Bargav and Evans, David}, + journal={arXiv preprint arXiv:2209.01292}, + year={2022} +} + + +@inproceedings{yeom, + author={Yeom, Samuel and Giacomelli, Irene and Fredrikson, Matt and Jha, Somesh}, + booktitle={IEEE Computer Security Foundations Symposium}, + title={Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting}, + year={2018}, + pages={268-282}, + doi={10.1109/CSF.2018.00027} +} + + +@inproceedings{Mahajan2020DoesLS, + title={Does Learning Stable Features Provide Privacy Benefits for Machine Learning Models?}, + author={Divyat Mahajan, Shruti Tople, Amit Sharma}, + booktitle = {NeurIPS PPML Workshop}, + year={2020} +} + +@inproceedings{Malekzadeh_2021, + doi = {10.1145/3460120.3484533}, + url = {https://doi.org/10.1145%2F3460120.3484533}, + year = 2021, month = {nov}, + publisher = {{ACM}}, + author = {Mohammad Malekzadeh and Anastasia Borovykh and Deniz Gündüz}, + title = {Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers{\textquotesingle} Outputs}, + booktitle = {Proceedings of the 2021 {ACM} {SIGSAC} Conference on Computer and Communications Security}} + + + +@INPROCEEDINGS{meminf, + author={Shokri, Reza and Stronati, Marco and Song, Congzheng and Shmatikov, Vitaly}, + booktitle={2017 IEEE Symposium on Security and Privacy (SP)}, + title={Membership Inference Attacks Against Machine Learning Models}, + year={2017}, + pages={3-18}, + doi={10.1109/SP.2017.41}} + +@article{chang2021privacy, + title={On the Privacy Risks of Algorithmic Fairness}, + author={Hongyang Chang and R. Shokri}, + journal={{2021 }IEEE European Symposium on Security and Privacy}, + year={2021}, + pages={292-303} +} + +@article{duddu2022inferring, + title={Inferring Sensitive Attributes from Model Explanations}, + author={Duddu, Vasisht and Boutet, Antoine}, + journal={arXiv preprint arXiv:2208.09967}, + year={2022} +} + +%editor = {H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin}, + %publisher = {Curran Associates, Inc.}, + %url = {https://proceedings.neurips.cc/paper/2020/file/6b8b8e3bd6ad94b985c1b1f1b7a94cb2-Paper.pdf}, +@inproceedings{NEURIPS2020_6b8b8e3b, + author = {Zhao, Han and Chi, Jianfeng and Tian, Yuan and Gordon, Geoffrey J}, + booktitle = {Advances in Neural Information Processing Systems}, + pages = {9485--9496}, + title = {Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation}, + volume = {33}, + year = {2020} +} + + + +@ARTICLE{8515092, +author={S. A. {Osia} and A. {Taheri} and A. S. {Shamsabadi} and K. {Katevas} and H. {Haddadi} and H. R. {Rabiee}}, +journal={IEEE Transactions on Knowledge and Data Engineering}, +title={Deep Private-Feature Extraction}, +year={2020}, +volume={32}, +number={1}, +pages={54-66}, +} + + + +%eprint = {1707.00075} +@article{advfair, + author = {Alex Beutel and Jilin Chen and Zhe Zhao and Ed H. Chi}, + title = {Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations}, + year = {2017}, + publisher = {arXiv}, + doi = {10.48550/ARXIV.1707.00075}, +} + +%property inference attack + +@article{propinf, + title={Dataset-Level Attribute Leakage in Collaborative Learning}, + author={Zhang, Wanrong and Tople, Shruti and Ohrimenko, Olga}, + journal={arXiv:2006.07267}, + year={2020} +} + +%month = sep, +@article{propinf2, +author = {Ateniese, Giuseppe and Mancini, Luigi V. and Spognardi, Angelo and Villani, Antonio and Vitali, Domenico and Felici, Giovanni}, +title = {Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers}, +year = {2015}, +volume = {10}, +number = {3}, +journal = {Int. J. Secur. Netw.}, +pages = {137–150} +} + + +%isbn = {9781450356930}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%url = {https://doi.org/10.1145/3243734.3243834}, +@inproceedings{propinf3, +author = {Ganju, Karan and Wang, Qi and Yang, Wei and Gunter, Carl A. and Borisov, Nikita}, +title = {Property Inference Attacks on Fully Connected Neural Networks Using Permutation Invariant Representations}, +year = {2018}, +doi = {10.1145/3243734.3243834}, +booktitle = {ACM SIGSAC Conference on Computer and Communications Security}, +pages = {619–633}, +location = {Toronto, Canada}, +series = {CCS '18} +} + +@article{propinf4, + title={Formalizing and Estimating Distribution Inference Risks}, + author={Suri, Anshuman and Evans, David}, + journal={Proceedings on Privacy Enhancing Technologies}, + year={2022} +} + +@inproceedings{fedinference, +author={L. {Melis} and C. {Song} and E. {De Cristofaro} and V. {Shmatikov}}, +booktitle={IEEE Symposium on Security and Privacy}, +title={Exploiting Unintended Feature Leakage in Collaborative Learning}, +year={2019}, +pages={691-706} +} + +@INPROCEEDINGS {ferryExploit, +author = {J. Ferry and U. Aivodji and S. Gambs and M. Huguet and M. Siala}, +booktitle = {2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)}, +title = {Exploiting Fairness to Enhance Sensitive Attributes Reconstruction}, +year = {2023}, +volume = {}, +issn = {}, +pages = {18-41}, +keywords = {training;measurement;learning systems;privacy;pipelines;training data;machine learning}, +doi = {10.1109/SaTML54575.2023.00012}, +url = {https://doi.ieeecomputersociety.org/10.1109/SaTML54575.2023.00012}, +publisher = {IEEE Computer Society}, +address = {Los Alamitos, CA, USA}, +month = {feb} +} + + + + +% defences against attribute inference attacks + +@inproceedings{10.5555/3042817.3042973, +author = {Zemel, Richard and Wu, Yu and Swersky, Kevin and Pitassi, Toniann and Dwork, Cynthia}, +title = {Learning Fair Representations}, +year = {2013}, +booktitle = {International Conference on Machine Learning}, +serie = {ICML '13}, +} + +%month = jan, +@article{10.5555/3122009.3208010, +author = {Hamm, Jihun}, +title = {Minimax Filter: Learning to Preserve Privacy from Inference Attacks}, +year = {2017}, +volume = {18}, +number = {1}, +journal = {J. Mach. Learn. Res.}, +pages = {4704–4734} +} + +@inproceedings{10.5555/3327546.3327583, +author = {Moyer, Daniel and Gao, Shuyang and Brekelmans, Rob and Steeg, Greg Ver and Galstyan, Aram}, +title = {Invariant Representations without Adversarial Training}, +year = {2018}, +booktitle = {Advances in Neural Information Processing Systems} +} + +@inproceedings{10.5555/3294771.3294827, +author = {Xie, Qizhe and Dai, Zihang and Du, Yulun and Hovy, Eduard and Neubig, Graham}, +title = {Controllable Invariance through Adversarial Feature Learning}, +year = {2017}, +booktitle = {Advances in Neural Information Processing Systems} +} + +@InProceedings{pmlr-v80-madras18a, + title = {Learning Adversarially Fair and Transferable Representations}, + author = {Madras, David and Creager, Elliot and Pitassi, Toniann and Zemel, Richard}, + pages = {3384--3393}, + year = {2018}, + volume = {80}, + booktitle = {Proceedings of Machine Learning Research}, +} + +@inproceedings{censoringadv, +title = "Censoring Representations with an Adversary", +author = "Harrison Edwards and Amos Storkey", +year = "2016", +booktitle = {International Conference on Learning Representations} +} +@inproceedings{NIPS2017_48ab2f9b, + author = {Louppe, Gilles and Kagan, Michael and Cranmer, Kyle}, + booktitle = {Advances in Neural Information Processing Systems}, + editor = {I. Guyon and U. Von Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett}, + pages = {}, + publisher = {Curran Associates, Inc.}, + title = {Learning to Pivot with Adversarial Networks}, + url = {https://proceedings.neurips.cc/paper_files/paper/2017/file/48ab2f9b45957ab574cf005eb8a76760-Paper.pdf}, + volume = {30}, + year = {2017} +} + + +%isbn = {9781450360128}, +%publisher = {Association for Computing Machinery}, +%address = {New York, NY, USA}, +%url = {https://doi.org/10.1145/3278721.3278779}, +@inproceedings{debiase, +author = {Zhang, Brian Hu and Lemoine, Blake and Mitchell, Margaret}, +title = {Mitigating Unwanted Biases with Adversarial Learning}, +year = {2018}, +doi = {10.1145/3278721.3278779}, +booktitle = {AAAI/ACM Conference on AI, Ethics, and Society}, +pages = {335–340}, +location = {New Orleans, LA, USA}, +series = {AIES '18} +} + + %month = {10}, +%pages = {}, +@article{preprocessing, +author = {Kamiran, Faisal and Calders, Toon}, +year = {2011}, +title = {Data Pre-Processing Techniques for Classification without Discrimination}, +volume = {33}, +journal = {Knowledge and Information Systems}, +doi = {10.1007/s10115-011-0463-8} +} + +%series = {Proceedings of Machine Learning Research}, + %month = {10--15 Jul}, + %publisher = {PMLR}, + %pdf = {http://proceedings.mlr.press/v80/agarwal18a/agarwal18a.pdf}, + %url = {https://proceedings.mlr.press/v80/agarwal18a.html}, +@InProceedings{reductions, + title = {A Reductions Approach to Fair Classification}, + author = {Agarwal, Alekh and Beygelzimer, Alina and Dudik, Miroslav and Langford, John and Wallach, Hanna}, + booktitle = {International Conference on Machine Learning}, + pages = {60--69}, + year = {2018}, + volume = {80}, +} + +@article{kifer2014pufferfish, +author = {Kifer, Daniel and Machanavajjhala, Ashwin}, +title = {Pufferfish: A framework for mathematical privacy definitions}, +year = {2014}, +issue_date = {January 2014}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +volume = {39}, +number = {1}, +issn = {0362-5915}, +url = {https://doi.org/10.1145/2514689}, +doi = {10.1145/2514689}, +journal = {ACM Trans. Database Syst.}, +month = {jan}, +articleno = {3}, +numpages = {36}, +keywords = {Privacy, differential privacy} +} + +@inproceedings{song2017pufferfish, + title={Pufferfish privacy mechanisms for correlated data}, + author={Song, Shuang and Wang, Yizhen and Chaudhuri, Kamalika}, + booktitle={Proceedings of the 2017 ACM International Conference on Management of Data}, + pages={1291--1306}, + year={2017} +} + +@article{grinsztajn2022tree, + title={Why do tree-based models still outperform deep learning on typical tabular data?}, + author={Grinsztajn, L{\'e}o and Oyallon, Edouard and Varoquaux, Ga{\"e}l}, + journal={Advances in neural information processing systems}, + volume={35}, + pages={507--520}, + year={2022} +} + + + +@inproceedings {attriguard, +author = {Jinyuan Jia and Neil Zhenqiang Gong}, +title = {AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning}, +booktitle = {USENIX Security}, +year = {2018}, +pages = {513--529}, +} + + +% fairness metrics + +@article{fairmetric, +author = {Muhammad Bilal Zafar and Isabel Valera and Manuel Gomez-Rodriguez and Krishna P. Gummadi}, +title = {Fairness Constraints: A Flexible Approach for Fair Classification}, +journal = {Journal of Machine Learning Research}, +year = {2019}, +volume = {20}, +number = {75}, +pages = {1-42} +} + +@inproceedings{fairmetric2, +author = {Hardt, Moritz and Price, Eric and Srebro, Nathan}, +title = {Equality of Opportunity in Supervised Learning}, +year = {2016}, +booktitle = {Advances in Neural Information Processing Systems}, +pages = {3323–3331} +} + +@article{fairjustice, +author = {Alikhademi, Kiana and Drobina, Emma and Prioleau, Diandra and Richardson, Brianna and Purves, Duncan and Gilbert, Juan E.}, +title = {A Review of Predictive Policing from the Perspective of Fairness}, +year = {2022}, +issue_date = {Mar 2022}, +publisher = {Kluwer Academic Publishers}, +address = {USA}, +volume = {30}, +number = {1}, +issn = {0924-8463}, +url = {https://doi.org/10.1007/s10506-021-09286-4}, +doi = {10.1007/s10506-021-09286-4}, +journal = {Artif. Intell. Law}, +month = {mar}, +pages = {1–17}, +numpages = {17}, +keywords = {Predictive policing, Algorithmic fairness, Fairness, AI in criminal justice} +} + + +@article{folk, + title={Retiring Adult: New Datasets for Fair Machine Learning}, + author={Ding, Frances and Hardt, Moritz and Miller, John and Schmidt, Ludwig}, + journal={Advances in Neural Information Processing Systems}, + volume={34}, + year={2021} +} + +@inproceedings{ + SDV, + title={The Synthetic data vault}, + author={Patki, Neha and Wedge, Roy and Veeramachaneni, Kalyan}, + booktitle={IEEE International Conference on Data Science and Advanced Analytics (DSAA)}, + year={2016}, + pages={399-410}, + doi={10.1109/DSAA.2016.49}, + month={Oct} +} + +@misc{dpbad, + doi = {10.48550/ARXIV.1104.3913}, + + url = {https://arxiv.org/abs/1104.3913}, + + author = {Dwork, Cynthia and Hardt, Moritz and Pitassi, Toniann and Reingold, Omer and Zemel, Rich}, + + keywords = {Computational Complexity (cs.CC), Computers and Society (cs.CY), FOS: Computer and information sciences, FOS: Computer and information sciences}, + + title = {Fairness Through Awareness}, + + publisher = {arXiv}, + + year = {2011}, + + copyright = {arXiv.org perpetual, non-exclusive license} +} + +@INPROCEEDINGS{fairlog, + + author={Radovanović, Sandro and Petrović, Andrija and Delibašić, Boris and Suknović, Milija}, + + booktitle={2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)}, + + title={Enforcing fairness in logistic regression algorithm}, + + year={2020}, + + volume={}, + + number={}, + + pages={1-7}, + + doi={10.1109/INISTA49547.2020.9194676}} + + +@misc{fairreg, + title={Fair Regression: Quantitative Definitions and Reduction-based Algorithms}, + author={Alekh Agarwal and Miroslav Dudík and Zhiwei Steven Wu}, + year={2019}, + eprint={1905.12843}, + archivePrefix={arXiv}, + primaryClass={cs.LG} +} + + + +@InProceedings{fairaudit1, + title = {Blind Justice: Fairness with Encrypted Sensitive Attributes}, + author = {Kilbertus, Niki and Gascon, Adria and Kusner, Matt and Veale, Michael and Gummadi, Krishna and Weller, Adrian}, + booktitle = {Proceedings of the 35th International Conference on Machine Learning}, + pages = {2630--2639}, + year = {2018}, + editor = {Dy, Jennifer and Krause, Andreas}, + volume = {80}, + series = {Proceedings of Machine Learning Research}, + month = {10--15 Jul}, + publisher = {PMLR}, + pdf = {http://proceedings.mlr.press/v80/kilbertus18a/kilbertus18a.pdf}, + url = {https://proceedings.mlr.press/v80/kilbertus18a.html}, +} + + +@inproceedings{fairaudit2, +author = {Park, Saerom and Kim, Seongmin and Lim, Yeon-sup}, +title = {Fairness Audit of Machine Learning Models with Confidential Computing}, +year = {2022}, +isbn = {9781450390965}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +url = {https://doi.org/10.1145/3485447.3512244}, +doi = {10.1145/3485447.3512244}, +booktitle = {Proceedings of the ACM Web Conference 2022}, +pages = {3488–3499}, +numpages = {12}, +keywords = {Confidential computing, Algorithmic audit, Security and privacy, Fairness}, +location = {Virtual Event, Lyon, France}, +series = {WWW '22} +} + +@inproceedings{fairaudit3, +author = {Segal, Shahar and Adi, Yossi and Pinkas, Benny and Baum, Carsten and Ganesh, Chaya and Keshet, Joseph}, +title = {Fairness in the Eyes of the Data: Certifying Machine-Learning Models}, +year = {2021}, +isbn = {9781450384735}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +url = {https://doi.org/10.1145/3461702.3462554}, +doi = {10.1145/3461702.3462554}, +booktitle = {Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society}, +pages = {926–935}, +numpages = {10}, +keywords = {machine-learning, cryptography, privacy, fairness}, +location = {Virtual Event, USA}, +series = {AIES '21} +} + +@article{yadav2024fairproof, + title={FairProof: Confidential and Certifiable Fairness for Neural Networks}, + author={Yadav, Chhavi and Chowdhury, Amrita Roy and Boneh, Dan and Chaudhuri, Kamalika}, + journal={arXiv preprint arXiv:2402.12572}, + year={2024} +} + +@inproceedings{khedr2023certifair, + title={Certifair: A framework for certified global fairness of neural networks}, + author={Khedr, Haitham and Shoukry, Yasser}, + booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, + volume={37}, + number={7}, + pages={8237--8245}, + year={2023} +} + +@article{urban20, +author = {Urban, Caterina and Christakis, Maria and W\"{u}stholz, Valentin and Zhang, Fuyuan}, +title = {Perfectly parallel fairness certification of neural networks}, +year = {2020}, +issue_date = {November 2020}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +volume = {4}, +number = {OOPSLA}, +journal = {Proc. ACM Program. Lang.}, +month = {nov}, +articleno = {185}, +numpages = {30}, +keywords = {Static Analysis, Neural Networks, Fairness, Abstract Interpretation} +} + +@inproceedings{ +chugg2023auditing, +title={Auditing Fairness by Betting}, +author={Ben Chugg and Santiago Cortes-Gomez and Bryan Wilder and Aaditya Ramdas}, +booktitle={Thirty-seventh Conference on Neural Information Processing Systems}, +year={2023}, +url={https://openreview.net/forum?id=EEVpt3dJQj} +} + +@inproceedings{yan2022active, + title={Active fairness auditing}, + author={Yan, Tom and Zhang, Chicheng}, + booktitle={International Conference on Machine Learning}, + pages={24929--24962}, + year={2022}, + organization={PMLR} +} + +@article{de2024fairness, + title={Fairness Auditing with Multi-Agent Collaboration}, + author={de Vos, Martijn and Dhasade, Akash and Bourr{\'e}e, Jade Garcia and Kermarrec, Anne-Marie and Merrer, Erwan Le and Rottembourg, Benoit and Tredan, Gilles}, + journal={arXiv preprint arXiv:2402.08522}, + year={2024} +} + +@inproceedings{ghosh2022algorithmic, + title={Algorithmic fairness verification with graphical models}, + author={Ghosh, Bishwamittra and Basu, Debabrota and Meel, Kuldeep S}, + booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, + volume={36}, + number={9}, + pages={9539--9548}, + year={2022} +} + +@inproceedings{ghosh2023biased, + title={“How Biased are Your Features?”: Computing Fairness Influence Functions with Global Sensitivity Analysis}, + author={Ghosh, Bishwamittra and Basu, Debabrota and Meel, Kuldeep S}, + booktitle={Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency}, + pages={138--148}, + year={2023} +} + +@article{FairSquare, +author = {Albarghouthi, Aws and D'Antoni, Loris and Drews, Samuel and Nori, Aditya V.}, +title = {FairSquare: probabilistic verification of program fairness}, +year = {2017}, +issue_date = {October 2017}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +volume = {1}, +number = {OOPSLA}, +url = {https://doi.org/10.1145/3133904}, +doi = {10.1145/3133904}, +journal = {Proc. ACM Program. Lang.}, +month = {oct}, +articleno = {80}, +numpages = {30}, +keywords = {Algorithmic Fairness, Probabilistic Inference, Probabilistic Programming} +} + +@article{saleiro2018aequitas, + title={Aequitas: A bias and fairness audit toolkit}, + author={Saleiro, Pedro and Kuester, Benedict and Hinkson, Loren and London, Jesse and Stevens, Abby and Anisfeld, Ari and Rodolfa, Kit T and Ghani, Rayid}, + journal={arXiv preprint arXiv:1811.05577}, + year={2018} +} + +@article{bastani2019probabilistic, + title={Probabilistic verification of fairness properties via concentration}, + author={Bastani, Osbert and Zhang, Xin and Solar-Lezama, Armando}, + journal={Proceedings of the ACM on Programming Languages}, + volume={3}, + number={OOPSLA}, + pages={1--27}, + year={2019}, + publisher={ACM New York, NY, USA} +} + +@article{adler2018auditing, + title={Auditing black-box models for indirect influence}, + author={Adler, Philip and Falk, Casey and Friedler, Sorelle A and Nix, Tionney and Rybeck, Gabriel and Scheidegger, Carlos and Smith, Brandon and Venkatasubramanian, Suresh}, + journal={Knowledge and Information Systems}, + volume={54}, + pages={95--122}, + year={2018}, + publisher={Springer} +} + +@inproceedings{black2020fliptest, + title={Fliptest: fairness testing via optimal transport}, + author={Black, Emily and Yeom, Samuel and Fredrikson, Matt}, + booktitle={Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency}, + pages={111--121}, + year={2020} +} + +@article{Justicia, +title={Justicia: A Stochastic SAT Approach to Formally Verify Fairness}, +volume={35}, +url={https://ojs.aaai.org/index.php/AAAI/article/view/16925}, DOI={10.1609/aaai.v35i9.16925}, +number={9}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Ghosh, Bishwamittra and Basu, Debabrota and Meel, Kuldeep S.}, year={2021}, month={May}, pages={7554-7563} }
\ No newline at end of file diff --git a/ACSAC/proofs/proof_advdebias.tex b/ACSAC/proofs/proof_advdebias.tex new file mode 100644 index 0000000..06212a0 --- /dev/null +++ b/ACSAC/proofs/proof_advdebias.tex @@ -0,0 +1,30 @@ +Definition~\ref{def:dp} of \dempar can be written synthetically as the following property: +$P_{\hat{Y},S}=P_{\hat{Y}}\otimes P_{S}$. +Where $P_{\hat{Y}}\otimes P_{S}$ is the product measure defined as the unique measure on +$\mathcal{P}(\mathcal{Y})\times\mathcal{P}(\mathcal{S})$ such that +$\forall y\in\mathcal{P}(\mathcal{Y})\forall s\in\mathcal{P}(\mathcal{S})\quad P_{\hat{Y}}\otimes P_{S}(y\times s) = P_{\hat{Y}}(y)P_{S}(s)$. +This is equivalent to definition~\ref{def:dp} for binary labels and sensitive attribute but more general because when $\hat{Y}$ is not binary as in soft labels, this new definition is well defined. +% We write formally +\begin{definition} +\label{def:dps} + $\hat{Y}$ satisfies extended \dempar for $S$ if and only if: $P_{\hat{Y},S}=P_{\hat{Y}}\otimes P_{S}$. +\end{definition} +This definition is the same as the statistical parity introduced for fair regression~\cite{fairreg}. +Note that we can not derive a quantity similar to \demparlevel with this definition but this extended \dempar assures indistinguishably of the sensitive attribute when looking at the soft labels. +We have the following theorem: +\begin{theorem}\label{th:advdebias} + The following propositions are equivalent: ``$\hat{Y}_s$ is independent of $S$'' and ``Balanced accuracy of \aia in \ref{tm:soft} is $\frac{1}{2}$'' +\end{theorem} +\begin{proof} +Let's show that it is equivalent to say "all attack models have a balanced accuracy of 0.5" and "the target model satisfies extended demographic parity". +{\footnotesize + \begin{align*} + &\forall a~P(\hat{Y}\in a^{-1}(\{0\})|S=0)+P(\hat{Y}\in a^{-1}(\{1\})|S=1) = 1\\ + \Leftrightarrow&\forall a~P(\hat{Y}\in a^{-1}(\{0\})|S=0)=P(\hat{Y}\in a^{-1}(\{0\})|S=1)\\ + \Leftrightarrow&\forall A~P(\hat{Y}\in A)|S=0)=P(\hat{Y}\in A|S=1) \\ + \Leftrightarrow &P_{\hat{Y},S}=P_{\hat{Y}}\otimes P_{S} + \end{align*} + } +\end{proof} + +%In conclusion, with extended \dempar we can not unconditionally bound the balanced accuracy of the attack without introducing distances in the space of distributions, but it gives us a condition to protect the sensitive attribute in case of an adversary gaining access to soft labels (AS).
\ No newline at end of file diff --git a/ACSAC/proofs/proof_egd_dp.tex b/ACSAC/proofs/proof_egd_dp.tex new file mode 100644 index 0000000..d0f23f6 --- /dev/null +++ b/ACSAC/proofs/proof_egd_dp.tex @@ -0,0 +1,33 @@ +\begin{theorem} +\label{th:dpgood} +Maximum attack accuracy achievable by \aia in \ref{tm:hard} is equal to $\frac{1}{2}(1+\text{\demparlevel of }\targetmodel)$. +\end{theorem} +\begin{proof} +The set $B$ of function from $\{0,1\}$ to $\{0,1\}$ contains four elements: $b_0=0$, $b_1=id$, $b_2=1-id$ and $b,3=1$, where $\forall x, id(x) = x$. +For every $b\in B$ the balanced \aia accuracy is +$BA(b) = \frac{1}{2}(P(b\circ \hat{Y}=0|S=0) + P(b\circ \hat{Y}=1|S=1))$. +We have $BA(b_0) = BA(b_3) = \frac{1}{2}$, hence, we can discard those elements when solving the attack optimisation problem. +This problem writes $\text{max}_{b\in B}B(A(b)) = \text{max}(BA(b_1), BA(b_2))$. +We remark that $b_1\circ \hat{Y}=\hat{Y}$ and $b_2\circ \hat{Y}=1 - \hat{Y}$. +Hence, +{\footnotesize +\begin{align*} + BA(b_1) &= \frac{1}{2}(P(\hat{Y}=0|S=0) + P(\hat{Y}=1|S=1))\\ + &=\frac{1}{2}(1+P(\hat{Y}=1|S=1) - P(\hat{Y}=1|S=0))\\ + BA(b_2)&=\frac{1}{2}(1+P(\hat{Y}=1|S=0) - P(\hat{Y}=1|S=1)) +\end{align*} +} +Thus, +{\footnotesize +\begin{align*} + &\text{max}_{b\in B}BA(b) + = \frac{1}{2}\left(1+\text{max}\left( + \begin{matrix} + P(\hat{Y}=0|S=0) -P(\hat{Y}=1|S=1)\\ + P(\hat{Y}=1|S=0) -P(\hat{Y}=0|S=1) + \end{matrix} + \right)\right)\\ + =&\frac{1}{2}(1+|P(\hat{Y}=1|S=1) - P(\hat{Y}=1|S=0)|) +\end{align*} +} +\end{proof} diff --git a/ACSAC/proofs/proof_egd_eo.tex b/ACSAC/proofs/proof_egd_eo.tex new file mode 100644 index 0000000..435add2 --- /dev/null +++ b/ACSAC/proofs/proof_egd_eo.tex @@ -0,0 +1,35 @@ +\begin{theorem} +\label{th:eoo} +If $\hat{Y}$ satisfies \eo for $Y$ and $S$ then the balanced accuracy of \aia in \ref{tm:hard} is $\frac{1}{2}$ iff $Y$ is independent of $S$ or $\hat{Y}$ is independent of $Y$. +\end{theorem} + +\begin{proof} +Let $\attackmodel$ be the attack model trained for AS: $\hat{S}=a\circ \hat{Y}$. +By the total probability formula +{\footnotesize +\begin{align*} +P(\hat{S}=0|S=0)=&P(\hat{S}=0|S=0Y=0)P(Y=0|S=0)\\ ++&P(\hat{S}=0|S=0Y=1)P(Y=1|S=0) +\end{align*} +} +and as well +{\footnotesize +\begin{align*} +P(\hat{S}=1|S=1)=&P(\hat{S}=1|S=1Y=0)P(Y=0|S=1)\\ + +&P(\hat{S}=1|S=1Y=1)P(Y=1|S=1) +\end{align*} +} +Then we substitute those terms in the definition of the balanced accuracy of $\targetmodel$. +{\footnotesize +\begin{align*} + &\frac{P(\hat{S}=0|S=0)+P(\hat{S}=1|S=1)}{2}\\ + =&\frac{1}{2}+\frac{1}{2}\left(P(Y=0|S=0)-P(Y=0|S=1)\right)\\ + &\left(P(\hat{Y}\in \attackmodel^{-1}(\{1\})|S=1Y=0) - + P(\hat{Y}\in \attackmodel^{-1}(\{1\})|S=1Y=1)\right) +\end{align*} +} +The balanced accuracy is equal to 0.5 if and only if $P(Y=0|S=0)=P(Y=0|S=1)$ +or $\forall \attackmodel~P(\hat{Y}\in \attackmodel^{-1}(\{1\})|S=1Y=0)=P(\hat{Y}\in \attackmodel^{-1}(\{1\})|S=1Y=1)$. +The first term indicates that $Y$ is independent of $S$ and the second term indicates that $S=1$ the $\targetmodel$ random guess utility. +We can do the same computing for $S=0$ and obtain a similar conclusion. +\end{proof}
\ No newline at end of file diff --git a/ACSAC/tables/tab_attack.tex b/ACSAC/tables/tab_attack.tex new file mode 100644 index 0000000..51974df --- /dev/null +++ b/ACSAC/tables/tab_attack.tex @@ -0,0 +1,30 @@ +\begin{table}[!htb] +%\vspace{-3mm} +\caption{\adaptiveAIAHard and \adaptiveAIASoft outperform their respective baselines. We report attack accuracy over ten runs.} +\begin{center} +%\footnotesize +\scriptsize +\begin{tabular}{ l | c | c } +\hline +\rowcolor{LightCyan} & \multicolumn{2}{c}{\ref{tm:hard}}\\ +\rowcolor{LightCyan} \textbf{Dataset} & \textbf{Baseline ($\upsilon$=0.50)} & \textbf{\adaptiveAIAHard}\\ +\rowcolor{LightCyan} & \textbf{\race} | \textbf{\sex}& \textbf{\race} | \textbf{\sex}\\ +\textbf{\census} & 0.50 $\pm$ 0.00 | 0.50 $\pm$ 0.00& \textbf{0.56 $\pm$ 0.01} | \textbf{0.58 $\pm$ 0.01} \\ +\textbf{\compas}& \textbf{0.62 $\pm$ 0.03} | 0.50 $\pm$ 0.00& \textbf{0.62 $\pm$ 0.03} | \textbf{0.57 $\pm$ 0.03} \\ +\textbf{\meps} & 0.51 $\pm$ 0.01 | \textbf{0.55 $\pm$ 0.02} & \textbf{0.53 $\pm$ 0.01} | \textbf{0.55 $\pm$ 0.01} \\ +\textbf{\lfw} & 0.59 $\pm$ 0.00 | 0.64 $\pm$ 0.15& \textbf{0.61 $\pm$ 0.11} | \textbf{0.78 $\pm$ 0.05} \\ +\hline +\rowcolor{LightCyan} & \multicolumn{2}{c}{\ref{tm:soft}} \\ +\rowcolor{LightCyan} \textbf{Dataset} & \textbf{Baseline ($\upsilon$=0.50)} & \textbf{\adaptiveAIASoft} \\ + \rowcolor{LightCyan} & \textbf{\race} | \textbf{\sex} & \textbf{\race} | \textbf{\sex}\\ +\hline +\textbf{\census}& 0.50 $\pm$ 0.02 | 0.56 $\pm$ 0.04 & \textbf{0.61 $\pm$ 0.02} | \textbf{0.68 $\pm$ 0.01} \\ +\textbf{\compas}& \textbf{0.62 $\pm$ 0.03} | 0.50 $\pm$ 0.00 & \textbf{0.62 $\pm$ 0.03} | \textbf{0.57 $\pm$ 0.03} \\ +\textbf{\meps} & 0.52 $\pm$ 0.02 | 0.55 $\pm$ 0.02 & \textbf{0.60 $\pm$ 0.02} | \textbf{0.62 $\pm$ 0.02}\\ +\textbf{\lfw} & 0.50 $\pm$ 0.10 | \textbf{0.77 $\pm$ 0.07} & \textbf{0.61 $\pm$ 0.10} | \textbf{0.79 $\pm$ 0.05}\\ +\hline +\end{tabular} +\end{center} +\label{tab:global_threshold_withoutsattr} +%\vspace{-5mm} +\end{table}
\ No newline at end of file diff --git a/ACSAC/tables/tab_datasets.tex b/ACSAC/tables/tab_datasets.tex new file mode 100644 index 0000000..3dfe024 --- /dev/null +++ b/ACSAC/tables/tab_datasets.tex @@ -0,0 +1,17 @@ +\begin{table}[htb] +\caption{Summary of dataset splits: $\traindata$ to train $\targetmodel$, $\testdata$ to evaluate $\targetmodel$, $\auxtraindata$ to train $\attackmodel$, and $\auxtestdata$ to evaluate $\attackmodel$.} +\footnotesize +\begin{center} +\begin{tabular}{ l | c | c | c | c} +\hline + \textbf{Dataset} & $\traindata$ & $\testdata$ & $\auxtraindata$ & $\auxtestdata$\\ + \hline + \textbf{\census} & 24,752 & 6,188 & 4,950 & 1,238 \\ + \textbf{\compas} & 4,937 & 1,235 & 988 & 247\\ + \textbf{\meps} & 12,664 & 3,166 & 2,532 & 634\\ + \textbf{\lfw} & 10514 & 2629 & 2103 & 526\\ + \hline +\end{tabular} +\end{center} +\label{tab:summary} +\end{table}
\ No newline at end of file diff --git a/ACSAC/tables/tab_summary.tex b/ACSAC/tables/tab_summary.tex new file mode 100644 index 0000000..f9598a4 --- /dev/null +++ b/ACSAC/tables/tab_summary.tex @@ -0,0 +1,32 @@ +\setlength\tabcolsep{3pt} +\begin{table*}[!htb] +\caption{Comparison of prior \aia{s}: attack vector exploited (e.g., $\targetmodel(X(\omega))$, $X(\omega)$, $Y(\omega)$, distribution over $S$ ($P_S$) and confusion matrix $C(Y,\targetmodel\circ X)$), whether $S$ is censored, i.e., included in $\traindata$ and inputs, whether \aia{s} account for class imbalance in $S$, whether \adv is active or passive and whether the threat model is blackbox or whitebox.} +\begin{center} +\footnotesize +% \resizebox{\textwidth}{!}{% +\begin{tabular}{ |c|c|c|c|c|c| } + \hline + \rowcolor{LightCyan} + \textbf{Literature} & \textbf{Attack Vector} & \textbf{Is $S$ censored?} & \textbf{Imbalance in $S$?} & \textbf{\adv} & \textbf{Threat Model} \\ + \hline + \rowcolor{LightCyan} + \multicolumn{6}{|c|}{\textbf{Imputation-based Attacks}}\\ + \hline + \textbf{Fredrikson et al.}~\cite{fredrikson2} & $X$, $Y$, $\targetmodel\circ X$, \textbf{$P_S$}, $C(Y,\targetmodel\circ X$) & $\checkmark$ & $\times$ & Passive & Blackbox\\ + \textbf{Yeom et al.}~\cite{yeom} & $X$, $Y$, $\targetmodel$, \textbf{$P_S$} & $\checkmark$ & $\times$ & Passive & Blackbox\\ + \textbf{Mehnaz et al.}~\cite{MehnazAttInf} & $X$, $Y$, $\targetmodel$, \textbf{$P_S$}, $C(Y,\targetmodel\circ X)$ & $\checkmark$ & $\times$ & Passive & Blackbox\\ + \textbf{Jayaraman and Evans}~\cite{jayaraman2022attribute} & $X$, $Y$, $\targetmodel$, $P_S$, $C(Y,\targetmodel\circ X)$ & $\times$, $\checkmark$ & $\times$ & Passive & Whitebox\\ + \hline + \rowcolor{LightCyan} + \multicolumn{6}{|c|}{\textbf{Representation-based Attacks}}\\ + \hline + \textbf{Song et al.}~\cite{Song2020Overlearning} & $\targetmodel\circ X$ & $\times$ & $\times$ & Passive & Both\\ + \textbf{Mahajan et al.}~\cite{Mahajan2020DoesLS} & $\targetmodel\circ X$ & $\checkmark$ & $\times$ & Passive & Blackbox\\ + \textbf{Malekzadeh et al.}~\cite{malekzadeh2021honestbutcurious} & $\targetmodel\circ X$ & $\times$ & $\times$ & Active & Blackbox\\ + % \textbf{Our Work} & $\targetmodel\circ X$ & $\times$, $\checkmark$ & $\checkmark$ & Passive & Blackbox \\ + \hline +\end{tabular} +% } +\end{center} +\label{tab:summary} +\end{table*}
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