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Diffstat (limited to 'ACSAC/proofs/proof_egd_eo.tex')
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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}
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