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Record W2049213423 · doi:10.1109/itng.2013.109

Public-Key Based Efficient Key Distribution in Bluetooth

2013· article· en· W2049213423 on OpenAlexaff
Saif Rahman, Yiruo He, Huapeng Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBluetooth and Wireless Communication Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBluetoothKey (lock)Computer scienceWirelessKey distributionMicroprocessorPublic-key cryptographyKey exchangeCryptographySide channel attackComputer securityEmbedded systemComputer networkTelecommunicationsEncryption

Abstract

fetched live from OpenAlex

Bluetooth provides short range low power wireless communication popularly between laptops, cellular phones and media devices. The original security measurement for Bluetooth looks somewhat inadequate today to meet many important security requirements. In this paper a public key technology based key distribution for Bluetooth is proposed. Taking advantage of `RSA for paranoids', the proposed method makes it possible for low-power and low computational capability embedded microprocessor to compute public-key technology based key distribution in reasonably short time. It is showed that the proposed method clearly has speed advantage when compared to the recent work on Bluetooth key exchange using Diffie-Hellman technology. The security of the proposed scheme against various attacks, including Gilbert's side-channel attack, is also addressed.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.219
Teacher spread0.192 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2013
Admission routes1
Has abstractyes

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