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Record W2152543840 · doi:10.1109/tpwrd.2010.2043122

Security Analysis and Auditing of IEC61850-Based Automated Substations

2010· article· en· W2152543840 on OpenAlexaff
Upeka Premaratne, Jagath Samarabandu, T.S. Sidhu, Robert Beresh, Jiancheng Tan

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2010
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsKinectrics (Canada)Western University
Fundersnot available
KeywordsAuditMetric (unit)Network securityComputer scienceInformation security auditComputer securityScheme (mathematics)Computer security modelNetwork Access ControlSecurity serviceInformation securityNetwork security policyEngineeringCloud computing securityAccountingMathematics

Abstract

fetched live from OpenAlex

This paper proposes a scheme for auditing the security of an IEC61850-based network based upon a novel security metric for intelligent electronic devices (IEDs). A detailed security analysis on an IEC61850 automated substation is peformed initially with a focus on the possible goals of the attacker. This is followed by the development of a scheme to audit the security of such a network. Security metrics are considered since they provide a tangible means of quantifying the security of a network. The proposed auditing scheme is tested by using it to audit the security of an IEC61850 network. The results are then compared with two other metric schemes-the mean time to compromise (MTTC) metric and the VEA-bility metric, which are used for auditing conventional computer networks. The input data for both metrics are obtained by using a network security tool to scan the IEDs of the network. The impact of using high-traffic generating network security tools on a time-critical IEC61850 network is also investigated.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.201
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2010
Admission routes1
Has abstractyes

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