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Record W1966156506 · doi:10.1109/icuwb.2015.7324413

A Survey on Cooperative Jamming Applied to Physical Layer Security

2015· article· en· W1966156506 on OpenAlexaff
Michael Atallah, Georges Kaddoum, Long Kong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsJammingEavesdroppingPhysical layerComputer scienceComputer securityComputer networkWirelessData link layerWireless networkTransmitterPhysical securityTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

Security has always played a critical role in wireless cooperative communication systems design. Eavesdropping and jamming are two common threats to the information security in wireless networks. However, jamming can be used in a cooperative manner to enable a secure communication link between the legitimate transmitter and the intended receiver. This paper presents a comprehensive survey on different jamming methods used to enhance the physical layer security. This survey outlines first the underlying concept and challenges with respect to security in wireless network design followed by a comprehensive literature review and analysis of jamming techniques with their applications in this field. For each jamming protocol, the paper categorizes different techniques within the existing literature by elaborating on their application, and corresponding performances.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.054
GPT teacher head0.299
Teacher spread0.245 · 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
GenreReview

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

Citations43
Published2015
Admission routes1
Has abstractyes

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