Generalized Rainbow Differential Privacy

arXiv:2309.05871v2 Announce Type: replace
Abstract: We study a new framework for designing differentially private (DP) mechanisms via randomized graph colorings, called rainbow differential privacy. In this framework, datasets are nodes in a graph, and two neighboring datasets are connected by an edge. Each dataset in the graph has a preferential ordering for the possible outputs of the mechanism, and these orderings are called rainbows. Different rainbows partition the graph of connected datasets into different regions. We show that if a …

arxiv called connected cs.cr cs.ir cs.it dataset datasets differential privacy edge framework graph math.it nodes privacy private study