We study natural privacy filters, which enable the exact composition of differentially private (DP) mechanisms with adaptively chosen privacy characteristics. Earlier privacy filters consider only simple privacy parameters such as Rényi-DP or Gaussian DP parameters. Natural filters account for the entire privacy profile of every query, promising greater utility for a given privacy budget. We show that, contrary to other forms of DP, natural privacy filters are not free in general. Indeed, we show that only families of privacy mechanisms that are well-ordered when composed admit free natural privacy filters.

翻译：本文研究自然隐私过滤器，其能够实现具有自适应选择隐私特性的差分隐私（DP）机制的精确组合。早期的隐私过滤器仅考虑简单的隐私参数，如Rényi-DP或高斯DP参数。自然过滤器则考虑每个查询的完整隐私轮廓，从而有望在给定隐私预算下获得更高的效用。我们证明，与其他形式的DP不同，自然隐私过滤器在一般情况下并非免费。具体而言，我们证明仅当隐私机制族在组合时具有良序性，才存在免费的自然隐私过滤器。