Distributed, Private, Sparse Histograms in the Two-Server Model: abstract simplified (18297084)

• This abstract for appeared for patent application number 18297084 Titled 'Distributed, Private, Sparse Histograms in the Two-Server Model'

Simplified Explanation

The abstract describes systems and methods for calculating sparse, (ε, δ)-differentially private histograms using a two-server model of secure multi-party computation. These protocols allow two servers to compute histograms over data from multiple users without colluding, while also maintaining the privacy of the data.

Original Abstract Submitted

Provided are systems and methods for the computation of sparse, (ε, δ)-differentially private (DP) histograms in the two-server model of secure multi-party computation (MPC). Example protocols enable two semi-honest non-colluding servers to compute histograms over the data held by multiple users, while only learning a private view of the data.