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Record W4401977969 · doi:10.3233/jhs-240075

Survey on securing wireless networks through a blockchain-based framework

2024· article· en· W4401977969 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

VenueJournal of High Speed Networks · 2024
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBlockchainComputer scienceComputer securityComputer networkWireless networkWirelessTelecommunications

Abstract

fetched live from OpenAlex

In the contemporary era, blockchain technology has brought about a significant transformation in the realm of digital currency through innovations like Bitcoin. A blockchain serves as a decentralized ledger, ensuring an immutable record of transactions across a network. Recent observations indicate the pivotal role of blockchain technology not only in the financial sector but also in networking. This study considers blockchain as the essential link in establishing a genuinely decentralized, trustless, and secure environment for network nodes. The objective is to provide a systematic and comprehensive overview of futuristic endeavours in this domain. The exploration begins with an examination of the fundamental operational concepts of blockchains and how these systems achieve decentralization, security, and suitability. The focus then shifts towards addressing open research challenges within blockchain technologies, particularly in securing diverse communication networks such as Distributed Computing, Vehicular Ad-hoc Networks, Opportunistic Networks, and Delay Tolerant Networks. Simulation results underscore the superior security performance of blockchain, especially under conditions of attack.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
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 head0.015
GPT teacher head0.259
Teacher spread0.244 · 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