We propose a distributed algorithm to compute an equilibrium in aggregate games where players communicate over a fixed undirected network. Our algorithm exploits correlated perturbation to obfuscate information shared over the network. We prove that our algorithm does not reveal private information of players to an honest-but-curious adversary who monitors several nodes in the network. In contrast with differential privacy based algorithms, our method does not sacrifice accuracy of equilibrium computation to provide privacy guarantees.
@article{arxiv.1912.06296,
title = {On Privatizing Equilibrium Computation in Aggregate Games over Networks},
author = {Shripad Gade and Anna Winnicki and Subhonmesh Bose},
journal= {arXiv preprint arXiv:1912.06296},
year = {2019}
}