This paper introduces the LDP-Auditor framework for empirically estimating
the privacy loss of Locally Differentially Private (LDP) mechanisms. Several
factors influencing the privacy audit are explored, such as the impact of
different encoding and perturbation functions of eight state-of-the-art LDP
protocols. Furthermore, the influence of domain size as well as the theoretical
privacy loss parameter ϵ on local privacy estimation are also
examined. Overall, our LDP-Auditor framework and findings offer valuable
insights into the sources of randomness and information loss in LDP protocols,
contributing to a more realistic understanding of the local privacy loss.
Furthermore, we demonstrate the effectiveness of LDP-Auditor by successfully
identifying a bug in an LDP library.Comment: Accepted for poster presentation at TPD