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Record W2962835128 · doi:10.1109/tcomm.2016.2591530

BER-Based Physical Layer Security With Finite Codelength: Combining Strong Converse and Error Amplification

2016· article· en· W2962835128 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 Transactions on Communications · 2016
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsQueen's University
Fundersnot available
KeywordsConverseBit error rateComputer scienceErasurePhysical layerAlgorithmBinary numberTransmission (telecommunications)Additive white Gaussian noiseDecoding methodsTopology (electrical circuits)Theoretical computer scienceMathematicsComputer networkChannel (broadcasting)TelecommunicationsArithmeticWirelessCombinatorics

Abstract

fetched live from OpenAlex

A bit-error-rate (BER)-based physical layer security approach is proposed for the finite blocklengths. For secure communication in the sense of high BER, the information-theoretic strong converse is combined with cryptographic error amplification achieved by the substitution permutation networks based on the confusion and diffusion. For the discrete memoryless channels (DMCs), an analytical framework is provided showing the tradeoffs among the finite blocklength, the maximum/minimum possible transmission rates, and the BER requirements for the legitimate receiver and the eavesdropper. In addition, the security gap is analytically studied for the Gaussian channels and the concept is extended to other DMCs including the binary symmetric channels and binary erasure channels.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.891
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.277
Teacher spread0.235 · 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