Detection and Mitigation of Biasing Attacks on Distributed Estimation Networks
Systems and Control
2018-10-11 v1
Abstract
The paper considers a problem of detecting and mitigating biasing attacks on networks of state observers targeting cooperative state estimation algorithms. The problem is cast within the recently developed framework of distributed estimation utilizing the vector dissipativity approach. The paper shows that a network of distributed observers can be endowed with an additional attack detection layer capable of detecting biasing attacks and correcting their effect on estimates produced by the network. An example is provided to illustrate the performance of the proposed distributed attack detector.
Cite
@article{arxiv.1810.04301,
title = {Detection and Mitigation of Biasing Attacks on Distributed Estimation Networks},
author = {Mohammad Deghat and Valery Ugrinovskii and Iman Shames and Cedric Langbort},
journal= {arXiv preprint arXiv:1810.04301},
year = {2018}
}
Comments
Accepted for publication in Automatica