We introduce a family of information leakage measures called maximal $\alpha,\beta$-leakage, parameterized by real numbers $\alpha$ and $\beta$. The measure is formalized via an operational definition involving an adversary guessing an unknown function of the data given the released data. We obtain a simple, computable expression for the measure and show that it satisfies several basic properties such as monotonicity in $\beta$ for a fixed $\alpha$, non-negativity, data processing inequalities, and additivity over independent releases. Finally, we highlight the relevance of this family by showing that it bridges several known leakage measures, including maximal $\alpha$-leakage $(\beta=1)$, maximal leakage $(\alpha=\infty,\beta=1)$, local differential privacy $(\alpha=\infty,\beta=\infty)$, and local Renyi differential privacy $(\alpha=\beta)$.
翻译:我们引入了一套信息泄漏措施,称为最大正负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负。 我们引入了一套信息泄漏措施,称为最大负负负负负负负负负负负负负负负负负负负负负负负负负负负负负。 最后,我们通过显示它连接了数种已知的泄漏措施,包括最大负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负(负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负负