MétaCan
Menu
Back to cohort

A Decentralized Hierarchical Key Management Scheme for Grid-Organized Wireless Sensor Networks (DHKM)

2020· article· en· W3045632086 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSecurity in Wireless Sensor Networks
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsKey managementComputer scienceComputer networkWireless sensor networkExploitOverhead (engineering)CryptographyDistributed computingKey (lock)Computer securityTrust management (information system)Scheme (mathematics)Cryptographic protocol

Abstract

fetched live from OpenAlex

Wireless Sensor Networks (WSNs) are attracted great attention in the past decade due to the unlimited number of applications they support. However, security has always been a serious concern for these networks due to the insecure communication links they exploit. In order to mitigate the possible security threats, sophisticated key management schemes must be employed to ensure the generating, distributing and revocation of the cryptographic keys that are needed to implement variety of security measures. In this paper, we propose a novel decentralized key management scheme for hierarchical grid organized WSNs. The main goal of our scheme is to reduce the total number of cryptographic keys stored in sensor nodes while maintaining the desired network connectivity. The performance analysis shows the efficiency of the proposed protocol in terms of communication overhead, storage cost and network connectivity.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.019
GPT teacher head0.238
Teacher spread0.218 · 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

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicSecurity in Wireless Sensor NetworksFrench-language works237,207