  We study the problem of collaboratively estimating the state of an LTI system
monitored by a network of sensors, subject to the following important practical
considerations: (i) certain sensors might be arbitrarily compromised by an
adversary and (ii) the underlying communication graph governing the flow of
information across sensors might be time-varying. We first analyze a scenario
involving intermittent communication losses that preserve certain information
flow patterns over bounded intervals of time. By equipping the sensors with
adequate memory, we show that one can obtain a fully distributed, provably
correct state estimation algorithm that accounts for arbitrary adversarial
behavior, provided certain conditions are met by the network topology. We then
argue that our approach can handle bounded communication delays as well. Next,
we explore a case where each communication link stochastically drops packets
based on an analog erasure channel model. For this setup, we propose state
estimate update and information exchange rules, along with conditions on the
network topology and packet drop probabilities, that guarantee mean-square
stability despite arbitrary adversarial attacks.
