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Record W2061534192 · doi:10.1109/glocom.2014.7036875

Relay authentication by exploiting I/Q imbalance in amplify-and-forward system

2014· article· en· W2061534192 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsRelayComputer scienceAuthentication (law)WirelessComputer networkTransmission (telecommunications)Fingerprint (computing)Computer securityTelecommunications

Abstract

fetched live from OpenAlex

Although cooperative relaying has been widely utilized in wireless communications, it simultaneously introduces a new source of security vulnerabilities to the wireless networks such as denial of service attacks. In order to minimize the potential security risks from relays, reliable relay authentication schemes become necessitated. In this paper, a novel relay authentication scheme is proposed to secure amplify-and-forward relay systems through utilizing the device-dependent hardware imperfection in-phase/quadrature (I/Q) imbalance. In this scheme, the I/Q imbalance associated with the receiving and transmission of the relaying process is considered as a unique device fingerprint. This fingerprint is then utilized to develop a two-parameter hypothesis testing based authentication. To enhance the performance in differentiating delicate difference between I/Q imbalances, the generalized likelihood ratio test for classical linear model is used in our hypothesis decision algorithm. The performance of the proposed authentication scheme is assessed and validated by numerical simulations. The results show significantly enhanced authentication accuracy of our new method in comparison with other I/Q imbalance based hypothesis decision algorithms.

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: Empirical
Teacher disagreement score0.905
Threshold uncertainty score0.353

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 science0.0000.000
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 head0.003
GPT teacher head0.185
Teacher spread0.182 · 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