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Cited by 1,285

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

False data injection attacks against state estimation in electric power grids

Liu, Yao, Ning, Peng, Reiter, Michael K.·2009·Proceedings of the 16th ACM conference on Computer and communications security

Abstract

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including the interacting bad measurements introduced by arbitrary, non-random causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers.

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Metadata

Authors
Liu, Y., Ning, P., & Reiter, M. K.
Venue
Proceedings of the 16th ACM conference on Computer and communications security
Publisher
ACM
Published
2009-11-09
Pages
21-32
ISSN
1543-7221 (ISSN-L)
OpenAlex
W2005028112
Cited by
1,285
References
1
FWCI
78.91
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: False data injection attacks against state estimation in electric power grids. https://app.cochat.ai/papers/10.1145/1653662.1653666
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Liu, Y., Ning, P., & Reiter, M. K. (2009). False data injection attacks against state estimation in electric power grids. Proceedings of the 16th ACM conference on Computer and communications security. https://doi.org/10.1145/1653662.1653666

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.