A Generalized Binary Tree Mechanism for Differentially Private Approximation of All-Pair Distances

Fuente: arXiv
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Autori principali: Dinitz, Michael, Fan, Chenglin, Liu, Jingcheng, Upadhyay, Jalaj, Zou, Zongrui
Natura: Preprint
Pubblicazione: 2025
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author Dinitz, Michael
Fan, Chenglin
Liu, Jingcheng
Upadhyay, Jalaj
Zou, Zongrui
author_facet Dinitz, Michael
Fan, Chenglin
Liu, Jingcheng
Upadhyay, Jalaj
Zou, Zongrui
contents We study the problem of approximating all-pair distances in a weighted undirected graph with differential privacy, introduced by Sealfon [Sea16]. Given a publicly known undirected graph, we treat the weights of edges as sensitive information, and two graphs are neighbors if their edge weights differ in one edge by at most one. We obtain efficient algorithms with significantly improved bounds on a broad class of graphs which we refer to as \textit{recursively separable}. In particular, for any $n$-vertex $K_h$-minor-free graph, our algorithm achieve an additive error of $\widetilde{O}(h(nW)^{1/3} ) $, where $ W $ represents the maximum edge weight; For grid graphs, the same algorithmic scheme achieve additive error of $\widetilde{O}(n^{1/4}\sqrt{W})$. Our approach can be seen as a generalization of the celebrated binary tree mechanism for range queries, as releasing range queries is equivalent to computing all-pair distances on a path graph. In essence, our approach is based on generalizing the binary tree mechanism to graphs that are \textit{recursively separable}.
format Preprint
id arxiv_https___arxiv_org_abs_2504_03354
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Generalized Binary Tree Mechanism for Differentially Private Approximation of All-Pair Distances
Dinitz, Michael
Fan, Chenglin
Liu, Jingcheng
Upadhyay, Jalaj
Zou, Zongrui
Data Structures and Algorithms
We study the problem of approximating all-pair distances in a weighted undirected graph with differential privacy, introduced by Sealfon [Sea16]. Given a publicly known undirected graph, we treat the weights of edges as sensitive information, and two graphs are neighbors if their edge weights differ in one edge by at most one. We obtain efficient algorithms with significantly improved bounds on a broad class of graphs which we refer to as \textit{recursively separable}. In particular, for any $n$-vertex $K_h$-minor-free graph, our algorithm achieve an additive error of $\widetilde{O}(h(nW)^{1/3} ) $, where $ W $ represents the maximum edge weight; For grid graphs, the same algorithmic scheme achieve additive error of $\widetilde{O}(n^{1/4}\sqrt{W})$. Our approach can be seen as a generalization of the celebrated binary tree mechanism for range queries, as releasing range queries is equivalent to computing all-pair distances on a path graph. In essence, our approach is based on generalizing the binary tree mechanism to graphs that are \textit{recursively separable}.
title A Generalized Binary Tree Mechanism for Differentially Private Approximation of All-Pair Distances
topic Data Structures and Algorithms
url https://arxiv.org/abs/2504.03354