  A network of observers is considered, where through asynchronous (with
bounded delay) communications, they cooperatively estimate the states of a
Linear Time-Invariant (LTI) system. In such a setting, a new type of adversary
might affect the observation process by impersonating the identity of the
regular node, which is a violation of communication authenticity. These
adversaries also inherit the capabilities of Byzantine nodes, making them more
powerful threats called smart spoofers. We show how asynchronous networks are
vulnerable to smart spoofing attack. In the estimation scheme considered in
this paper, information flows from the sets of source nodes, which can detect a
portion of the state variables each, to the other follower nodes. The regular
nodes, to avoid being misguided by the threats, distributively filter the
extreme values received from the nodes in their neighborhood. Topological
conditions based on strong robustness are proposed to guarantee the
convergence. Two simulation scenarios are provided to verify the results.
