期刊
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
卷 13, 期 11, 页码 2816-2830出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIFS.2018.2831619
关键词
Differential privacy; Hamming distortion; information leakage; utility-privacy tradeoff
资金
- National Science Foundation [CIF-1422358, CCF-1453432, SaTC-1617849]
- DARPA
- SSC Pacific [N66001-15-C-4070]
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [1453432] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1422358] Funding Source: National Science Foundation
A privacy-utility tradeoff is developed for an arbitrary set of finite-alphabet source distributions. Privacy is quantified using differential privacy (DP), and utility is quantified using expected Hamming distortion maximized over the set of distributions. The family of source distribution sets (source sets) is categorized into three classes, based on different levels of prior knowledge they capture. For source sets whose convex hull includes the uniform distribution, symmetric DP mechanisms are optimal. For source sets whose probability values have a fixed monotonic ordering, asymmetric DP mechanisms are optimal. For all other source sets, general upper and lower bounds on the optimal privacy leakage are developed and necessary and sufficient conditions for tightness are established. Differentially private leakage is an upper bound on mutual information leakage: the two criteria are compared analytically and numerically to illustrate the effect of adopting a stronger privacy criterion.
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