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.
@article{arxiv.1609.05300,
title = {Detection of Biasing Attacks on Distributed Estimation Networks},
author = {Mohammad Deghat and Valery Ugrinovskii and Iman Shames and Cedric Langbort},
journal= {arXiv preprint arXiv:1609.05300},
year = {2016}
}
Comments
The paper is to appear in Proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, December 2016