모수적 부트스트랩을 이용한 차등정보보호 히스토그램의 동질성 검정

Abstract

We propose a test of consistency for two differentially private histograms using parametric bootstrap. The test can be applied when the original raw histograms are not available but only the differentially private histograms and the privacy level a are available. We also extend the test for the case where the privacy levels are different for different histograms. The resident population data of Korea and U.S in year 2020 are used to demonstrate the efficacy of the proposed test procedure. The proposed test controls the type I error rate at the nominal level and has a high power, while a conventional test procedure fails. While the differential privacy framework formally controls the risk of privacy leakage, the utility of such framework is questionable. This work also suggests that the power of a carefully designed test may be a viable measure of utility.