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Record W2041267417 · doi:10.1504/ijcis.2011.042974

Quantitative estimates of critical infrastructures' interdependencies on the communication and information technology infrastructure

2011· article· en· W2041267417 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Critical Infrastructures · 2011
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInterdependenceCritical infrastructureComputer scienceRanking (information retrieval)Critical infrastructure protectionInformation systemComputer securityRisk analysis (engineering)Operations researchSystems engineeringEngineeringBusiness

Abstract

fetched live from OpenAlex

Interdependencies of critical infrastructures on communications and information technology infrastructure (CITI) are known collectively as cyber interdependency, which has significant impact on many critical infrastructures. However, till now no formal relationship has been proposed to estimate cyber interdependencies. In this paper, we present a set of empirical functions to represent cyber interdependencies for different critical infrastructures. Our approach is based on identifying important CITI services for each of these infrastructures and systematically ranking them according to their contribution to the infrastructures’ output. The description of interdependencies between infrastructure entities in functional form is rooted in system theory and is an essential component of computational modelling and simulation. The work presented in this paper is a pioneering attempt to formalise cyber interdependencies for different critical infrastructures from a system engineering approach.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.003
Open science0.0020.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.299
Teacher spread0.283 · 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