A fundamental problem in differential privacy is to release a privatized data structure over a dataset that can be used to answer a class of linear queries with small errors. This problem has been well studied in the static case. In this paper, we consider the dynamic setting where items may be inserted into or deleted from the dataset over time, and we need to continually release data structures so that queries can be answered at any time instance. We present black-box constructions of such dynamic differentially private mechanisms from static ones with only a polylogarithmic degradation in the utility. For the fully-dynamic case, this is the first such result. For the insertion-only case, similar constructions are known, but we improve them for sparse update streams.

翻译：差异隐私的一个基本问题是在一个数据集上发布一个私有化的数据结构,该数据集可用于回答一系列线性查询,但有小错误。这个问题在静态案例中得到了很好的研究。在本文中,我们考虑了可长期插入或从数据集中删除项目动态设置,我们需要不断发布数据结构,以便随时可以回答查询。我们展示了从静态的、具有不同动态的私人机制的黑盒结构,这些机制在工具中只有多元性退化。对于完全动态的个案来说,这是第一个这样的结果。对于只插入的个案来说,类似的构造是已知的,但我们为稀疏的更新流改进了它们。