  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.
