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Record W2906097308 · doi:10.1109/mie.2018.2874385

Physical-Layer Security for Industrial Wireless Control Systems: Basics and Future Directions

2018· article· en· W2906097308 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 Industrial Electronics Magazine · 2018
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsUniversity of Waterloo
FundersNational Key Research and Development Program of ChinaVINNOVANational Natural Science Foundation of China
KeywordsPHYWirelessPhysical layerComputer scienceWireless networkIndustrial control systemReliability (semiconductor)Computer networkControl (management)Telecommunications

Abstract

fetched live from OpenAlex

Wireless networks for industrial control systems are promising because of their reduced cost, flexible structure, and improved long-term reliability. However, wireless control systems are vulnerable to probing-free attacks (PFAs), which are not possible in wired control systems. Thus, wireless control systems must be made as secure as wired systems. Physical (PHY)-layer security technology (PHY-Sec) may be a new strategy for securing industrial wireless control systems. Among all PHY-Sec technologies, PHY-layer authentication is the first step for PHYSec in industrial wireless control systems. This article discusses the principles of PHY-Sec, its application to wireless control systems, and potential research directions.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.236
Teacher spread0.218 · 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