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Record W1998697412 · doi:10.1109/mcom.2012.6194395

Balance of security strength and energy for a PMU monitoring system in smart grid

2012· article· en· W1998697412 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

VenueIEEE Communications Magazine · 2012
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsComputer scienceSmart gridOverhead (engineering)Secure communicationWireless sensor networkEmbedded systemComputer networkComputer securityDistributed computingElectrical engineeringEncryptionEngineering

Abstract

fetched live from OpenAlex

An efficient dependable smart power grid relies on the secure real-time data collection and transmission service provided by a monitoring system. In such a system, the measuring units, such as phasor measurement units (PMUs) and smart meters (SMs), are critical. These measuring equipments function as sensors in the smart grid. Data exchanges between these sensors and the central controller are protected by various security protocols. These protocols usually contain computationally intensive cryptographic algorithms that cause heavy energy overhead to the sensor nodes. Since PMUs and SMs are mostly energy-constrained, the problem of how to ensure the secure communication with minimum energy cost becomes a critical issue for the functionality of the whole smart grid. In this article, we focus on the low power secure communication of the PMUs and SMs. We take two wireless sensor platforms as examples to experimentally investigate the approaches and principles of reconciling the two conflicting system requirements-communication security and low energy consumptions. The proposed methods are general ones and applicable to other energy-constrained yet security sensitive systems.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.248
Teacher spread0.231 · 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