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Record W3152504018 · doi:10.1109/msmc.2020.3049092

Observer-Based Attack Detection and Mitigation for Cyberphysical Systems: A Review

2021· review· en· W3152504018 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Systems Man and Cybernetics Magazine · 2021
Typereview
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSCADACyber-physical systemSoftware deploymentComputer scienceWireless sensor networkVulnerability (computing)Computer securityActuatorIndustrial control systemEmbedded systemDistributed computingControl (management)Computer networkEngineeringArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

Demands for security, efficiency, and environmental protection have led to the rapid deployment of cyberphysical systems (CPSs), which are now an integral part of modern industries. Wireless sensor networks (WSNs), which provide distributed intelligent devices for monitoring physical and environmental conditions, are a CPS hallmark. CPSs often consist of distributed devices, such as sensors and actuators, to connect with and influence physical layer systems. Commonly, CPSs are monitored by supervisory control and data acquisition (SCADA) systems. Integrating cyber and physical worlds facilitates more effective and efficient CPS operation. However, the gains come at the price of cyberattack vulnerability.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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 head0.035
GPT teacher head0.284
Teacher spread0.249 · 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