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Record W2047068440 · doi:10.4271/2012-01-2103

Novel Approach for Securing Air-Ground Communication

2012· article· en· W2047068440 on OpenAlexaff
Aniruddha R. Karmarkar

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2012
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The FAA and other Air Navigation Service Providers (ANSPs) plan to share the existing cockpit data radio for NextGen data communication applications. This radio is currently used for supporting airline operations. Sharing this radio, which operates in a relatively open network environment, with mission critical air traffic control communications creates a need to address air-ground security. Most of the data to be shared over air-ground communication is tactical and transient in nature. In addition, secure communication between the controller and the pilot provides situational awareness to all receivers listening on the voice radio channel. In this paper we provide a rationale for securing air-ground communication and explore some of the issues in implementing a secure air-ground communication channel between the controller and the pilot over the shared radio. We recommend a lightweight approach based on Identity Based Encryption (IBE) that meets the security paradigms of confidentiality, integrity, and availability of the system without compromising situational awareness.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.262
Teacher spread0.237 · 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 designBench or experimental
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

Citations0
Published2012
Admission routes1
Has abstractyes

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