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A detection and mitigation model for PTP delay attack in a smart grid substation

2015· article· en· W2309038109 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
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceSmart gridProtocol (science)Computer securityGridMechanism (biology)Computer networkEmbedded systemReal-time computingDistributed computingEngineering

Abstract

fetched live from OpenAlex

Smart grid applications demand the availability of a reliable and accurate time signal. Measurements and events need to be correctly aligned to enable proper actions and decisions. Precision Time Protocol (PTP) is the favored protocol for time distribution across smart grid domains. The correct functionality of PTP is of paramount importance and its security is of high priority. To harden its security, detection and prevention mechanisms against attacks targeting PTP are needed. In this paper, we propose detection and mitigation mechanisms against the known PTP delay attack. We apply model checking to quantify the effect of the delay attack. Moreover, the validity of the proposed mechanism is formally proven. The collected results support the usefulness of the mechanism in detecting the delay attacks targeting PTP, and preserving the system functionality.

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: Methods · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.273

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 communication0.0000.001
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 head0.036
GPT teacher head0.262
Teacher spread0.227 · 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

Quick stats

Citations12
Published2015
Admission routes1
Has abstractyes

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