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Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks i...

Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks i...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2379945503

Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks in Power Systems

About this item

Full title

Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks in Power Systems

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2022-08

Language

English

Formats

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

More information

Scope and Contents

Contents

Power system functionality is determined on the basis of the power system state estimation (PSSE). Thus, corruption of the PSSE may lead to severe consequences, such as financial losses, maintenance damage, and disruptions in electricity distribution. Classical bad data detection (BDD) methods, developed to ensure PSSE reliability, are unable to de...

Alternative Titles

Full title

Structural-constrained Methods for the Identification of Unobservable False Data Injection Attacks in Power Systems

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2379945503

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2379945503

Other Identifiers

E-ISSN

2331-8422

DOI

10.48550/arxiv.2003.08715

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