Visible to the public On the Impact of Trusted Nodes in Resilient Distributed State Estimation of LTI Systems

TitleOn the Impact of Trusted Nodes in Resilient Distributed State Estimation of LTI Systems
Publication TypeConference Paper
Year of Publication2018
AuthorsMitra, Aritra, Abbas, Waseem, Sundaram, Shreyas
Conference Name2018 IEEE Conference on Decision and Control (CDC)
Date PublishedDec. 2018
PublisherIEEE
ISBN Number978-1-5386-1395-5
Keywordsattack-prone environment, attack-resilient algorithm, communication-link augmentation, computational complexity, computer network security, computer theory, Heuristic algorithms, human factors, linear dynamical process, Linear systems, LTI systems, Measurement, NP-hard, provably-correct distributed state estimation algorithm, pubcrawl, Redundancy, resilience, Resiliency, resilient distributed state estimation, Robustness, Scalability, security, Sensors, set theory, state estimation, Trusted Computing, trusted nodes
Abstract

We address the problem of distributed state estimation of a linear dynamical process in an attack-prone environment. A network of sensors, some of which can be compromised by adversaries, aim to estimate the state of the process. In this context, we investigate the impact of making a small subset of the nodes immune to attacks, or "trusted". Given a set of trusted nodes, we identify separate necessary and sufficient conditions for resilient distributed state estimation. We use such conditions to illustrate how even a small trusted set can achieve a desired degree of robustness (where the robustness metric is specific to the problem under consideration) that could otherwise only be achieved via additional measurement and communication-link augmentation. We then establish that, unfortunately, the problem of selecting trusted nodes is NP-hard. Finally, we develop an attack-resilient, provably-correct distributed state estimation algorithm that appropriately leverages the presence of the trusted nodes.

URLhttps://ieeexplore.ieee.org/document/8619772
DOI10.1109/CDC.2018.8619772
Citation Keymitra_impact_2018