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Record W2119782732 · doi:10.1109/ccece.2008.4564831

Network security authentication of power system operations

2008· article· en· W2119782732 on OpenAlexaffvenue
Helen Cheung, Alexander Hamlyn, Cungang Yang

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicAccess Control and Trust
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceAuthentication (law)Network Access ControlSmart gridDistributed System Security ArchitectureNetwork securityComputer networkComputer securityEnterprise information security architectureComputer security modelKey (lock)Electric power systemDistributed computingPower (physics)Cloud computing securityEngineeringOperating systemElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents a new strategy for computer network security authentication of power system operations. Recently operations of electricity power distribution systems have become fairly complex due to introduction of distributed generations and microgrids, execution of open access competition, increased use of network-controlled devices, etc. Computer network therefore turns into a key integral of modern power-grid operations. This paper proposes a new utility computer network security authentication of requests for actions / commands in the smart-grid operations. The authentication covers multiple security domains in a new security architecture designed for smart power grids. This paper presents the strategy and platform of security authentications of requests for operations in the host area electric power system (AEPS) and interconnected multiple neighboring AEPS. Case studies of the new security authentication for smart grids operations are presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.212
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 source (direct Gemma or distilled Codex), 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

Citations5
Published2008
Admission routes2
Has abstractyes

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