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Record W3048531936 · doi:10.23977/jeis.2020.51003

An efficient revocable ID-Based key insulated signature scheme to achieve authentication of smart meter

2020· article· en· W3048531936 on OpenAlexvenueno aff
Shaomin Zhang, Zejiao Shao, Baoyi Wang

Bibliographic record

VenueJournal of Electronics and Information Science · 2020
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsnot available
Fundersnot available
KeywordsSmart meterSmart gridKey (lock)Public-key cryptographyScheme (mathematics)Authentication (law)Computer scienceComputer networkSignature (topology)Computer securitySmart cardComputationMessage authentication codeCryptographyEngineeringEncryptionElectrical engineeringMathematicsAlgorithm

Abstract

fetched live from OpenAlex

In the smart grid, a large number of smart meters distributed at the edge of the network transmit electricity data to the control center through public network. Therefore, it is crucial to authenticate smart meter. Traditional authentication schemes that based on signature are usually rely on the assumption that the private key is absolutely secure, and private key exposure will endanger the security of the whole scheme. Further, most of these schemes are designed with bilinear pairings, which results in a high cost in computation and communication. So, an efficient revocable ID-based key insulated signature scheme is proposed in this paper. Computational analysis shows that our scheme has less cost than other schemes in computation and communication, which is suitable for smart meters with limited computational capability. Besides, our scheme can revoke the misbehaving or malicious smart meter conveniently and quickly.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.000
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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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