Cluster-based resilient distributed estimation through adversary detection
journal contribution
posted on 2020-01-01, 00:00 authored by F Gao, Q Yu, L Bai, J Wang, Jinho Choi© The Institution of Engineering and Technology 2019. Security becomes increasingly important due to various attacks from adversaries in wireless sensor networks. This work considers a resilient distributed estimation of an unknown parameter with a cluster-based approach when some agents are adversarial. A two-phase algorithm is adopted to perform parameter estimation and detect attacks. First, a cluster scheme is proposed to make sure that each cluster is connected. Then, the attack is detected and estimation is achieved with a consensus +innovation estimator in each cluster. Finally, the cluster heads combine the consensus estimates in each cluster and exchange with other cluster heads to achieve unknown parameter estimation. In addition, the detection sensitivity under different cluster schemes is also compared. Numerical examples illustrate that the proposed cluster-based approach can improve the convergence rate and detection sensitivity.
History
Journal
IET CommunicationsVolume
14Pagination
451-457Location
Stevenage, Eng.Publisher DOI
Open access
- Yes
Link to full text
ISSN
1751-8628Language
engPublication classification
C1 Refereed article in a scholarly journalIssue
3Publisher
Institution of Engineering and TechnologyUsage metrics
Categories
Keywords
Licence
Exports
RefWorksRefWorks
BibTeXBibTeX
Ref. managerRef. manager
EndnoteEndnote
DataCiteDataCite
NLMNLM
DCDC