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Record W1996225565 · doi:10.1109/tetc.2013.2273220

A Wormhole Attack Resistant Neighbor Discovery Scheme With RDMA Protocol for 60 GHz Directional Network

2013· article· en· W1996225565 on OpenAlexaff
Zhiguo Shi, Ruixue Sun, Rongxing Lu, Jian Qiao, Jiming Chen, Xuemin Shen

Bibliographic record

VenueIEEE Transactions on Emerging Topics in Computing · 2013
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsComputer scienceComputer networkNeighbor Discovery ProtocolRemote direct memory accessAuthentication (law)Broadcasting (networking)Message authentication codeComputer securityInternet ProtocolThe InternetCryptographyOperating system

Abstract

fetched live from OpenAlex

In this paper, we propose a wormhole attack resistant secure neighbor discovery (SND) scheme for a centralized 60-GHz directional wireless network. Specifically, the proposed SND scheme consists of three phases: the network controller (NC) broadcasting phase, the network nodes response/authentication phase, and the NC time analysis phase. In the broadcasting phase and the response/authentication phase, local time information and antenna direction information are elegantly exchanged with signature-based authentication techniques between the NC and the legislate network nodes, which can prevent most of the wormhole attacks. In the NC time analysis phase, the NC can further detect the possible attack using the time-delay information from the network nodes. To solve the transmission collision problem in the response/authentication phase, we also introduce a novel random delay multiple access (RDMA) protocol to divide the RA phase into M periods, within which the unsuccessfully transmitting nodes randomly select a time slot to transmit. The optimal parameter setting of the RDMA protocol and the optional strategies of the NC are discussed. Both neighbor discovery time analysis and security analysis demonstrate the efficiency and effectiveness of the proposed SND scheme in conjunction with the RDMA protocol.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.272
Teacher spread0.249 · 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 designSimulation or modeling
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

Citations11
Published2013
Admission routes1
Has abstractyes

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