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Record W2352592412

A Grou PKey Management Scheme Based on Secret Sharing in WSNs

2010· article· en· W2352592412 on OpenAlexvenueno aff
LV Yuanfang

Bibliographic record

VenueMicrocomputer applications · 2010
Typearticle
Languageen
FieldComputer Science
TopicSecurity in Wireless Sensor Networks
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSecrecyForward secrecyComputer networkOverhead (engineering)EncryptionKey managementWireless sensor networkSecret sharingSymmetric-key algorithmKey (lock)Node (physics)Computer securityKey distributionDistributed computingPublic-key cryptographyCryptography
DOInot available

Abstract

fetched live from OpenAlex

A grou Pkey management scheme based on secret sharing in wireless sensor network is proposed, which is called GKMSSS. GKMSSS uses LEACH protocol to make the network clustering. Based on the theory of secret sharing and the principle of symmetric key encryption, the grou Pkey components are stored in the various grou Pmembers in a distributed manner. And the key pre-configured, hierarchical key generation, the network sub-clusters, key generation and distribution, key updates, grou Pof new members joining and members of the grou Pexiting are successfully achieved. Through correlation analysis and experiments, it shows that GKMSSS effectively assures the grou Pcommunication forward secrecy, backward secrecy and good anti-prisoner capacity of the node on condition that the storage overhead and communication overhead is in an acceptable situation respectively.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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