Composition in Differential Privacy for General Granularity Notions (Long Version)

arXiv:2308.14649v2 Announce Type: replace
Abstract: The composition theorems of differential privacy (DP) allow data curators to combine different algorithms to obtain a new algorithm that continues to satisfy DP. However, new granularity notions (i.e., neighborhood definitions), data domains, and composition settings have appeared in the literature that the classical composition theorems do not cover. For instance, the original parallel composition theorem does not translate well to general granularity notions. This complicates the opportunity of composing DP mechanisms in new settings …

algorithm algorithms arxiv cs.cr cs.ds data definitions differential privacy domains general literature privacy settings version