On privatizing equilibrium computation in aggregate games over networks

Shripad Gade, Anna Winnicki, Subhonmesh Bose

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)3272-3277
Number of pages6
Issue number2
StatePublished - 2020
Event21st IFAC World Congress 2020 - Berlin, Germany
Duration: Jul 12 2020Jul 17 2020


  • Nash equilibrium computation
  • Networked aggregate games
  • Privacy

ASJC Scopus subject areas

  • Control and Systems Engineering


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