  We present a distributed average consensus protocol that preserves the
privacy of agents' inputs. Unlike the differential privacy mechanisms, the
presented protocol does not affect the accuracy of the output. It is shown that
the protocol preserves the information-theoretic privacy of the agents' inputs
against colluding passive adversarial (or honest-but-curious) agents in the
network, if the adversarial agents do not constitute a vertex cut in the
underlying communication network. This implies that we can guarantee
information-theoretic privacy of all the honest agents' inputs against $t$
arbitrary colluding passive adversarial agents if the network is
$(t+1)$-connected. The protocol is constructed by composing a distributed
privacy mechanism that we propose with any (non-private) distributed average
consensus algorithm.
