Abstract | ||
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We study the setup where each of $n$ users holds an element from a discrete set, and the goal is to count the number of distinct elements across all users, under the constraint of $(\epsilon, \delta)$-differentially privacy: - In the non-interactive local setting, we prove that the additive error of any protocol is $\Omega(n)$ for any constant $\epsilon$ and for any $\delta$ inverse polynomial in $n$. - In the single-message shuffle setting, we prove a lower bound of $\Omega(n)$ on the error for any constant $\epsilon$ and for some $\delta$ inverse quasi-polynomial in $n$. We do so by building on the moment-matching method from the literature on distribution estimation. - In the multi-message shuffle setting, we give a protocol with at most one message per user in expectation and with an error of $\tilde{O}(\sqrt(n))$ for any constant $\epsilon$ and for any $\delta$ inverse polynomial in $n$. Our protocol is also robustly shuffle private, and our error of $\sqrt(n)$ matches a known lower bound for such protocols. Our proof technique relies on a new notion, that we call dominated protocols, and which can also be used to obtain the first non-trivial lower bounds against multi-message shuffle protocols for the well-studied problems of selection and learning parity. Our first lower bound for estimating the number of distinct elements provides the first $\omega(\sqrt(n))$ separation between global sensitivity and error in local differential privacy, thus answering an open question of Vadhan (2017). We also provide a simple construction that gives $\tilde{\Omega}(n)$ separation between global sensitivity and error in two-party differential privacy, thereby answering an open question of McGregor et al. (2011). |
Year | DOI | Venue |
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2021 | 10.4230/LIPIcs.ITCS.2021.56 | ITCS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Lijie Chen | 1 | 18 | 6.90 |
Badih Ghazi | 2 | 88 | 15.07 |
Ravi Kumar | 3 | 13932 | 1642.48 |
Pasin Manurangsi | 4 | 62 | 28.79 |