Detection of biasing attacks on distributed estimation networks
Mohammad Deghat, Valery Ugrinovskii, Iman Shames, Cédric Langbort · 2016
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∞approach.