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Record W2775635164 · doi:10.1109/mvt.2017.2752760

Secure Group Communications in Vehicular Networks: A Software-Defined Network-Enabled Architecture and Solution

2017· article· en· W2775635164 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

VenueIEEE Vehicular Technology Magazine · 2017
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer networkComputer scienceCommunication in small groupsPlatoonVehicular ad hoc networkNetwork architectureComputer securityArchitectureEnterprise information security architectureThe InternetTelecommunicationsWireless ad hoc networkWirelessWorld Wide Web

Abstract

fetched live from OpenAlex

As a means to improve road safety and efficiency and to provide high-performance data transmission service for vehicular networks, group-based vehicular communications (e.g., platoon) has attracted a lot of attention from both academia and industry. In this article, we introduce group-based vehicular communication and address two major security challenges: 1) securely and dynamically setting up and managing the group for a decentralized network, which guarantees the confidentiality and integrity of information being exchanged among vehicles; and 2) secure group access and mobility management for the centralized network, which enables group members to securely and efficiently access the Internet, especially while moving across heterogeneous networks. We propose an integrated network architecture for secure group communication, taking advantage of the software-defined network (SDN) technology in fifth generation (5G) mobile networks.

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: Empirical
Teacher disagreement score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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