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Record W2023291727 · doi:10.1109/milcom.2012.6415724

LAA: Link-layer anonymous access for tactical MANETs

2012· article· en· W2023291727 on OpenAlexaff
Ronggong Song, Helen Tang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsComputer networkComputer scienceMobile ad hoc networkNode (physics)Wireless ad hoc networkLink layerNetwork packetKey managementVehicular ad hoc networkKey (lock)AnonymityData link layerAuthentication (law)Computer securityWirelessPhysical layerTelecommunicationsEncryptionEngineering

Abstract

fetched live from OpenAlex

Link layer security has been widely researched in the last decade as a means of protecting wireless networks (e.g., WEP, RSN, WPA, WPA2). However, there is little research in this area for Mobile Ad Hoc Networks (MANETs), especially for tactical MANETs. Although RSN can be used for MANETs as described in the IEEE 802.11i standard, it fails to meet some requirements of tactical MANETs, such as strong security, anonymity, and quick connectivity. In this paper, we propose a link layer anonymous access protocol (LAA) in order to provide strong security and anonymity protection for tactical MANETs. The protocol uses dynamic pseudonyms as network and node identities for network access authentication to prevent tracking, tracing, and other common attacks. It uses a localized key management mechanism for local shared key and broadcast key establishment that outperforms the connectivity and efficiency of key management in RSN and other link layer security technologies such as SEAMAN. Simulations show that LAA has only a small effect on end-to-end delay and no effect on packet delivery ratio relative to the standard MAC, meanwhile providing anonymous communication, better protection and improved connectivity performance in the link layer for tactical MANETs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.424

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 communication0.0000.001
Open science0.0010.000
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 head0.053
GPT teacher head0.328
Teacher spread0.275 · 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 designNot applicable
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

Citations4
Published2012
Admission routes1
Has abstractyes

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