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Record W1970818505 · doi:10.1109/msp.2008.9

Estimating a System's Mean Time-to-Compromise

2008· article· en· W1970818505 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 Security & Privacy · 2008
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsCompromiseSCADAMetric (unit)Computer scienceInterval (graph theory)Duration (music)State (computer science)State spaceMathematicsAlgorithmStatisticsEngineeringLawOperations management

Abstract

fetched live from OpenAlex

Mean time-to-compromise is a comparative security metric that applies lessons learned from physical security. To address this need in the SCADA world specifically and the corporate IT security world more generally, we propose a mean time-to-compromise (MTTC) interval as an estimate of the time it will take for an attacker with a specific skill level to successfully impact a target system. We also propose a state-space model (SSM) and algorithms for estimating attack paths and state times to calculate these MTTC intervals for a given target system. Although we use SCADA as an example, we believe our approach should work in any IT environment.

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), Insufficient payload (model declined to judge)
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 score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.006

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 head0.014
GPT teacher head0.233
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