Differentially private average consensus with general directed graphs.

Differential privacy, a strict privacy notion, prevents the presence or absence of a single data from being identified. This paper proposes a novel average consensus algorithm to achieve differentially private average consensus on multi-agent systems (MASs) with general directed graphs. For MASs under the proposed algorithm, necessary and sufficient conditions are established on achieving average consensus and preserving differential privacy of the states of the agents at any time instant. Finally, numerical examples are provided to illustrate these results. [ABSTRACT FROM AUTHOR]