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Record W1898035851 · doi:10.1002/sec.726

Password-authenticated cluster-based group key agreement for smart grid communication

2013· article· en· W1898035851 on OpenAlexafffund
Hasen Nicanfar, Victor C. M. Leung

Bibliographic record

VenueSecurity and Communication Networks · 2013
Typearticle
Languageen
FieldComputer Science
TopicSecurity in Wireless Sensor Networks
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceGroup keyForward secrecyPasswordCommunication in small groupsKey (lock)SecrecyComputer securityKey-agreement protocolProtocol (science)Scheme (mathematics)Key exchangeComputer networkContext (archaeology)Secure communicationKey managementCryptographyPublic-key cryptographyKey distributionEncryption

Abstract

fetched live from OpenAlex

Several multiparty systems supporting group-based and cloud-based applications have been proposed in the context of smart grid. An important requirement of these systems is that the devices/parties need to communicate with each other as members of a group. In this paper, we present an efficient group key GK management scheme aimed at securing the group communications, for instance, from the utility to appliances and smart meters located in different homes. Our scheme is based on the X.1035 password-authenticated key exchange protocol standard and also follows the cluster-based approach to reduce the costs of the GK construction and maintenance for large groups. Our protocol enables secure communications utilizing any communication technology. Analysis using one of the best evaluation tools in the technical community shows that our constructed GK is valid and secure against well-known attacks. We also show that the proposed scheme supports forward and backward secrecy and is more efficient in comparison with other GK mechanisms in the literature. Copyright © 2013 John Wiley & Sons, Ltd.

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)0.004
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 score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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

Citations18
Published2013
Admission routes2
Has abstractyes

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