Poster

Counting Distinct Elements Under Person-Level Differential Privacy

Thomas Steinke · Alexander Knop

Great Hall & Hall B1+B2 (level 1) #1612
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Thu 14 Dec 3 p.m. PST — 5 p.m. PST

Abstract:

We study the problem of counting the number of distinct elements in a dataset subject to the constraint of differential privacy. We consider the challenging setting of person-level DP (a.k.a. user-level DP) where each person may contribute an unbounded number of items and hence the sensitivity is unbounded.Our approach is to compute a bounded-sensitivity version of this query, which reduces to solving a max-flow problem. The sensitivity bound is optimized to balance the noise we must add to privatize the answer against the error of the approximation of the bounded-sensitivity query to the true number of unique elements.

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