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Differentially Private Average Consensus: Obstructions, Trade-Offs, and Optimal Algorithm Design
This paper studies the multi-agent average consensus problem under the requirement of differential privacy of the agents’ initial states against an adversary that has access to all the messages. We first establish that a differentially private consensus algorithm cannot guarantee convergence of the agents’ states to the exact average in distribution, which in turn implies the same impossibility for other stronger notions of convergence.
Submitted by Jorge Cortes on October 13th, 2017