Publications (11)
On Computing Pairwise Statistics with Local Differential Privacy
Badih Ghazi, Pritish Kamath, Ravi Kumar +2
We study the problem of computing pairwise statistics, i.e., ones of the form , where denotes the input to the th user, with…
Optimizing Hierarchical Queries for the Attribution Reporting API
Matthew Dawson, Badih Ghazi, Pritish Kamath +8
We study the task of performing hierarchical queries based on summary reports from the {\em Attribution Reporting API} for ad conversion measurement. We demonstrate that methods fr…
Urania: Differentially Private Insights into AI Use
Daogao Liu, Edith Cohen, Badih Ghazi +8
We introduce , a novel framework for generating insights about LLM chatbot interactions with rigorous differential privacy (DP) guarantees. The framework employs a private…
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar +2
In this work, we give a new technique for analyzing individualized privacy accounting via the following simple observation: if an algorithm is one-sided add-DP, then its subsampled…
Population stability: regulating size in the presence of an adversary
Shafi Goldwasser, Rafail Ostrovsky, Alessandra Scafuro +1
We introduce a new coordination problem in distributed computing that we call the population stability problem. A system of agents each with limited memory and communication, as we…
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy
Adam Sealfon, Jonathan Ullman
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)---wi…