Making Differential Privacy Easier to Use for Data Controllers and Data Analysts using a Privacy Risk Indicator and an Escrow-Based Platform

arXiv:2310.13104v2 Announce Type: replace-cross
Abstract: Differential privacy (DP) enables private data analysis but is hard to use in practice. For data controllers who decide what output to release, choosing the amount of noise to add to the output is a non-trivial task because of the difficulty of interpreting the privacy parameter $\epsilon$. For data analysts who submit queries, it is hard to understand the impact of the noise introduced by DP on their tasks.
To address these two challenges: 1) …

analysis analysts arxiv controllers cs.cr cs.db data data analysis data analysts differential privacy easier escrow hard making noise platform practice privacy privacy risk private private data release risk