Disclosure Risk from Homogeneity Attack in Differentially Private Frequency Distribution. (arXiv:2101.00311v4 [cs.CR] UPDATED)

Differential privacy (DP) provides a robust model to achieve privacy
guarantees for released information. We examine the protection potency of
sanitized multi-dimensional frequency distributions via DP randomization
mechanisms against homogeneity attack (HA). HA allows adversaries to obtain the
exact values on sensitive attributes for their targets without having to
identify them from the released data. We propose measures for disclosure risk
from HA and derive closed-form relationships between the privacy loss
parameters in DP and the disclosure risk from HA. …

adversaries attack attributes data differential privacy disclosure distribution distributions identify information privacy private protection randomization relationships risk