research-article

Distributed Kalman filtering for robust state estimation over wireless sensor networks under malicious cyber attacks

Authors:

Zhongmin WangAuthors Info & Claims

Volume 78, Issue C

Pages 92 - 97

https://doi.org/10.1016/j.dsp.2018.03.002

Published: 01 July 2018 Publication History

Abstract

We consider distributed Kalman filtering for dynamic state estimation over wireless sensor networks. It is promising but challenging when network is under cyber attacks. The compromised nodes are likely to influence system security by broadcasting malicious false measurements or estimates to their neighbors, and result in performance deterioration. To increase network resilience to cyber attacks, in this paper, trust-based dynamic combination strategy is developed. The proposed distributed Kalman filtering scheme is resilient to random, false data injection and replay attacks. Furthermore, it is efficient in terms of communication load, only instantaneous estimates are exchanged between the neighboring nodes and compromised nodes localization is a byproduct.

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Cited By

Segovia-Ferreira MRubio-Hernan JCavalli AGarcia-Alfaro J(2024)A Survey on Cyber-Resilience Approaches for Cyber-Physical SystemsACM Computing Surveys10.1145/365295356:8(1-37)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3652953
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Aydin MKozat S(2022)A hybrid framework for sequential data prediction with end-to-end optimizationDigital Signal Processing10.1016/j.dsp.2022.103687129:COnline publication date: 1-Sep-2022
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Distributed Kalman filtering for robust state estimation over wireless sensor networks under malicious cyber attacks

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Published In

cover image Digital Signal Processing

Digital Signal Processing Volume 78, Issue C

Jul 2018

404 pages

ISSN:1051-2004

Issue’s Table of Contents

Elsevier Inc.

Publisher

Academic Press, Inc.

United States

Publication History

Published: 01 July 2018

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Cited By

Segovia-Ferreira MRubio-Hernan JCavalli AGarcia-Alfaro J(2024)A Survey on Cyber-Resilience Approaches for Cyber-Physical SystemsACM Computing Surveys10.1145/365295356:8(1-37)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3652953
Zhang YWang GPeng SLeng YWang B(2024)Near-field beamforming method based on motion model analysis for UAVs communicationDigital Signal Processing10.1016/j.dsp.2024.104478149:COnline publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1016/j.dsp.2024.104478
Aydin MKozat S(2022)A hybrid framework for sequential data prediction with end-to-end optimizationDigital Signal Processing10.1016/j.dsp.2022.103687129:COnline publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1016/j.dsp.2022.103687
Yu YLiang Y(2022)Secure multitarget tracking over decentralized sensor networks with malicious cyber attacksDigital Signal Processing10.1016/j.dsp.2021.103132117:COnline publication date: 22-Apr-2022
https://dl.acm.org/doi/10.1016/j.dsp.2021.103132
Zheng XWu H(2021)Robust filtering algorithm against hybrid-attacks and randomly occurring nonlinearitiesDigital Signal Processing10.1016/j.dsp.2021.103159117:COnline publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1016/j.dsp.2021.103159
Pan RTan YDu DFei S(2020)Adaptive event-triggered synchronization control for complex networks with quantization and cyber-attacksNeurocomputing10.1016/j.neucom.2019.11.096382:C(249-258)Online publication date: 21-Mar-2020
https://dl.acm.org/doi/10.1016/j.neucom.2019.11.096

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