Cited by 595Smart Grid Security and ResiliencePower System Optimization and StabilitySmart Grid and Power Systems

Vulnerability Assessment of AC State Estimation With Respect to False Data Injection Cyber-Attacks

Hug, Gabriela, Giampapa, Joseph Andrew·2012·IEEE Transactions on Smart Grid

Abstract

This paper introduces new analytical techniques for performing vulnerability analysis of state estimation when it is subject to a hidden false data injection cyber-attack on a power grid's SCADA system. Specifically, we consider ac state estimation and describe how the physical properties of the system can be used as an advantage in protecting the power system from such an attack. We present an algorithm based on graph theory which allows determining how many and which measurement signals an attacker will attack in order to minimize his efforts in keeping the attack hidden from bad data detection. This provides guidance on which measurements are vulnerable and need increased protection. Hence, this paper provides insights into the vulnerabilities but also the inherent strengths provided by ac state estimation and network topology features such as buses without power injections.

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Crossref · 10.1109/tsg.2012.2195338

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  • DNP3 has vulnerabilities and its packets can be analysed through network sniffing tools to gain information and cause damage.

    “Other recent protocols, such as Distributed Network Protocol 3.0 (DNP3) also have their vulnerabilities [5], [38], [39] and packets can also be analysed [36] through network sniffing tools to gain information and cause damage.”
  • A simple flooding attack fills the event buffer in the data aggregator so that critical alerts from legitimate devices cannot be buffered, impacting the control station's situational awareness.

    “A simple flooding attack fills the event buffer in the data aggregator so that the critical alerts from legitimate devices cannot be buffered which impacts the control station's situational awareness.”

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Authors
Hug, G., & Giampapa, J. A.
Affiliations
  • Carnegie Mellon University (US)
  • Software Engineering Institute (US)
Venue
IEEE Transactions on Smart Grid
Published
2012-09
Volume
3
Issue
3
Pages
1362-1370
ISSN
  • 1949-3053 (ISSN-L)
  • 1949-3061
OpenAlex
W2022810949
Cited by
595
References
0
Citations by year
2026: 24 · 2025: 29 · 2024: 43 · 2023: 44 · 2022: 59 · 2021: 55 · 2020: 72 · 2019: 64 · 2018: 65 · 2017: 50 · 2016: 40 · 2015: 23 · 2014: 16 · 2013: 11
FWCI
23.19
Type
journal article
Language
en
Open access
closed
Locations
IEEE Transactions on Smart Grid (publishedVersion)
Funders
  • U.S. Department of Defense (FA8721-05-C-0003)
  • U.S. Department of Energy
  • Carnegie Mellon University
  • Australian Government
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Power System Optimization and Stability
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
Keywords
false data injection attacks, AC state estimation, SCADA security, vulnerability assessment, bad data detection, graph theory, measurement selection, network topology, power system protection

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