The DOI matches its Crossref record; 10 of the 11 references it cites were found in a registry or an index.
Quantitative Cyber Risk Reduction Estimation Methodology for a Small SCADA Control System
Open accessAbstract
We propose a new methodology for obtaining a quantitative measurement of the risk reduction achieved when a control system is modified with the intent to improve cyber security defense against external attackers. The proposed methodology employs a directed graph called a compromise graph, where the nodes represent stages of a potential attack and the edges represent the expected time-to-compromise for differing attacker skill levels. Time-to-compromise is modeled as a function of known vulnerabilities and attacker skill level. The methodology was used to calculate risk reduction estimates for a specific SCADA system and for a specific set of control system security remedial actions. Despite an 86% reduction in the total number of vulnerabilities, the estimated time-to-compromise was increased only by about 3 to 30% depending on target and attacker skill level.
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In the citing paper
“Among the triad, integrity and availability are highly paramount, while confidentiality is secondary for SCADA systems (Cheminod et al., 2013; McQueen et al., 2006).”
From A review of cyber security risk assessment methods for SCADA systems (2016) · cites this paper as McQueen et al., 2006
In the citing paper
“Only in two papers, namely McQueen et al. (2006) and Patel and Zaveri (2010), it is explicitly mentioned that the method was applied to a real system.”
From A review of cyber security risk assessment methods for SCADA systems (2016) · cites this paper as McQueen et al. (2006)
In the citing paper
“The authors of the methods examined point out that data required for the effective estimation of risk are rarely avail-able (Dondossola et al., 2009; McQueen et al., 2006) and, therefore, research often has to rely on artificial data (Luiijf et al., 2009).”
From A review of cyber security risk assessment methods for SCADA systems (2016) · cites this paper as McQueen et al., 2006
In the citing paper
“There are though several proposals (Henry and Haimes, 2009; LeMay et al., 2011; McQueen et al., 2006; Patel et al., 2008), which we mark with regarding risk evaluation in Table 7, where the comparison of risk metrics is performed between differ-ent security configurations of a system.”
From A review of cyber security risk assessment methods for SCADA systems (2016) · cites this paper as McQueen et al., 2006
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Metadata
- Authors
- McQueen, M. A., Boyer, W. F., Flynn, M. A., & Beitel, G. A.
- Affiliations
- Idaho National Laboratory (US)
- Venue
- Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06)
- Publisher
- IEEE
- Published
- 2006
- Pages
- 226-226
- ISSN
- 1530-1605 (ISSN-L)
- OpenAlex
- W2113310679
- Cited by
- 104
- References
- 11
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 5 · 2022: 3 · 2021: 3 · 2020: 5 · 2019: 11 · 2018: 6 · 2017: 6 · 2016: 3 · 2015: 8 · 2014: 7 · 2013: 11 · 2012: 3
- FWCI
- 8.56
- Type
- conference paper
- Language
- en
- Open access
- green
- www.osti.gov
- Locations
- Hawaii International Conference on System Sciences (HICSS) (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- University of North Texas Digital Library (University of North Texas) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Resilience and Vulnerability Analysis
- Keywords
- cyber risk reduction, SCADA systems, vulnerability remediation, directed graph modeling, quantitative risk assessment, industrial control systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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