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Record W4210984421 · doi:10.1109/sin54109.2021.9699265

Cut It: Deauthentication Attack on Bluetooth

2021· article· en· W4210984421 on OpenAlexaff
Karim Lounis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBluetooth and Wireless Communication Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsBluetoothVulnerability (computing)Computer scienceComputer securityWirelessDisconnectionVulnerability assessmentComputer networkEmbedded systemTelecommunications

Abstract

fetched live from OpenAlex

Bluetooth is a short-range wireless communication technology that is widely used nowadays. It has been deployed in millions of devices including laptops, watches, mobile phones, cars, printers, and many other smart devices. Although Bluetooth provides some security mechanisms, the technology is still subject to various types of attacks. In this paper, we present a security vulnerability that we have discovered on many Bluetooth devices. This vulnerability can be exploited to generate a deauthentication attack on paired Bluetooth devices causing their disconnection. In contrary to many other Bluetooth attacks that require certain skills and budget for their generation, the attack that we present in this paper does only require ordinary skills, cheap hardware, and free software. The security vulnerability is due to an implementation flaw in the way existing Bluetooth connections are handled, rather than a flaw in the Bluetooth specification (IEEE 802.15.1). We demonstrate through various attack patterns how the vulnerability can be exploited to cause deauthentication and disconnection of Bluetooth devices. Also, we discuss and recommend possible options to address the vulnerability.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.060
GPT teacher head0.305
Teacher spread0.245 · 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 designTheoretical or conceptual
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

Citations4
Published2021
Admission routes1
Has abstractyes

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