  In this paper we propose a novel method for achieving average consensus in a
continuous-time multiagent network while avoiding to disclose the initial
states of the individual agents. In order to achieve privacy protection of the
state variables, we introduce maps, called output masks, which alter the value
of the states before transmitting them. These output masks are local (i.e.,
implemented independently by each agent), deterministic, time-varying and
converging asymptotically to the true state. The resulting masked system is
also time-varying and has the original (unmasked) system as its limit system.
It is shown in the paper that the masked system has the original average
consensus value as a global attractor. However, in order to preserve privacy,
it cannot share an equilibrium point with the unmasked system, meaning that in
the masked system the global attractor cannot be also stable.
