论文标题
不对称的本地信息隐私和监督机制
Asymmetric Local Information Privacy and the Watchdog Mechanism
论文作者
论文摘要
本文通过概括本地信息隐私（LIP）来增强数据实用程序，提出了一种新颖的监视私有化计划。为了保护敏感功能$ s $与一些有用的数据相关，唇限制了升力，后验信念与访问$ x $之前的$ s $的比率。对于每个$ x $，敏感功能上的最大和最小提升都是发布此符号的隐私风险的度量，应限制出于隐私的目的。以前的作品对Max-Lift和Min-Lift都强制执行相同的界限。但是，经验观察表明，最小升级通常比最大升级小得多。在这项工作中，我们将唇部定义概括为考虑最大和最小升力的不等值，即考虑到最大升级和最小升级的不同界限。该新定义应用于监督隐私机制。我们证明，在对当地差异隐私的给定隐私约束下，该公用事业已得到增强。同时，最终的最大升级较低，因此严格限制了其他隐私泄漏，例如共同信息，最大泄漏和$α$ -leakage。
This paper proposes a novel watchdog privatization scheme by generalizing local information privacy (LIP) to enhance data utility. To protect the sensitive features $S$ correlated with some useful data $X$, LIP restricts the lift, the ratio of the posterior belief to the prior on $S$ after and before accessing $X$. For each $x$, both maximum and minimum lift over sensitive features are measures of the privacy risk of publishing this symbol and should be restricted for the privacy-preserving purpose. Previous works enforce the same bound for both max-lift and min-lift. However, empirical observations show that the min-lift is usually much smaller than the max-lift. In this work, we generalize the LIP definition to consider the unequal values of max and min lift, i.e., considering different bounds for max-lift and min-lift. This new definition is applied to the watchdog privacy mechanism. We demonstrate that the utility is enhanced under a given privacy constraint on local differential privacy. At the same time, the resulting max-lift is lower and, therefore, tightly restricts other privacy leakages, e.g., mutual information, maximal leakage, and $α$-leakage.
