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Record W2901354401 · doi:10.1002/rnc.4419

Security analysis for cyber‐physical systems under undetectable attacks: A geometric approach

2018· article· en· W2901354401 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

VenueInternational Journal of Robust and Nonlinear Control · 2018
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsUniversity of Alberta
FundersMinistry of Industry and Information Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsUnobservableSubspace topologyComputer scienceCyber-physical systemComputer securityActuatorProcess (computing)Feed forwardSecurity analysisSecurity controlsControl theory (sociology)Control (management)Control engineeringArtificial intelligenceEngineeringMathematics

Abstract

fetched live from OpenAlex

Summary In this paper, the security issues of cyber‐physical systems under undetectable attacks are studied. The geometric control theory is used to investigate the design, implementation, and impact evaluation of undetectable attacks. First, a feedforward‐feedback structure for undetectable attacks is proposed, which provides a designable form for an attack to be undetectable. The corresponding attack strategy is designed via pole placement in the weakly unobservable subspace of the attacked system. Then, the security analysis of several common undetectable attacks injected from actuators, sensors, and the coordinated of the two is discussed. Finally, the simulations on the quadruple‐tank process demonstrate the effectiveness of the proposed methods.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.499
Threshold uncertainty score0.395

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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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