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Record W2097731133 · doi:10.1002/sat.1038

Security in DVB‐RCS2

2013· article· en· W2097731133 on OpenAlexaff
Mark Bowyer, L. Erup, Hans Peter Lexow

Bibliographic record

VenueInternational Journal of Satellite Communications and Networking · 2013
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsAdvantech AMT (Canada)
Fundersnot available
KeywordsComputer scienceDigital Video BroadcastingTelecommunicationsReturn channelDigital televisionComputer securityBroadcasting (networking)Channel (broadcasting)

Abstract

fetched live from OpenAlex

SUMMARY This paper presents security features in the second generation digital video broadcasting with return channel via satellite standard (DVB‐RCS2). The up‐front consideration of security, and in particular transmission security (TRANSEC), started with the development of security requirements introduced in the DVB‐RCS Next Generation (NG) Commercial Requirements and Call for Technologies. It was apparent at an early stage that no single approach or implementation would satisfy the wide range of product and security requirements to span consumer, professional and government market sectors. This led to the introduction and development of two important concepts: TRANSEC profiles, a specialization of DVB‐RCS2 system level profiles concept; and TRANSEC ‘hooks’, extension points that allow TRANSEC functionality to be added as necessary, governed by profile security requirements. The bulk of this paper outlines and describes the three TRANSEC profiles presented in the DVB‐RCS2 Lower Layer Guidelines document. Finally, the various profiles are compared and contrasted. Copyright © 2013 John Wiley & Sons, Ltd.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.028

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 communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.004

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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2013
Admission routes1
Has abstractyes

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