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arXiv · 1905.10477

Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy

Adam Sealfon·Jonathan Ullman
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Abstract

We give a simple, computationally efficient, and node-differentially-private algorithm for estimating the parameter of an Erdos-Renyi graph---that is, estimating p in a G(n,p)---with near-optimal accuracy. Our algorithm nearly matches the information-theoretically optimal exponential-time algorithm for the same problem due to Borgs et al. (FOCS 2018). More generally, we give an optimal, computationally efficient, private algorithm for estimating the edge-density of any graph whose degree distribution is concentrated on a small interval.

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Adam Sealfon, Jonathan Ullman. 2019-05-24. Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy. https://arxiv.org/abs/1905.10477

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