Detection of Biasing Attacks on Distributed Estimation Networks
  The paper addresses the problem of detecting attacks on distributed estimator networks that aim to intentionally bias process estimates produced by the network. It provides a sufficient condition, in terms of the feasibility of certain linear matrix inequalities, which guarantees distributed input attack detection using an $H_\infty$ approach. 
Mohammad Deghat, Valery Ugrinovskii, Iman Shames, Cedric Langbort
cs.SY