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Record W2012405741 · doi:10.5539/cis.v2n2p112

A Model of Intrusion Tolerant System Based on Game Theory

2009· article· en· W2012405741 on OpenAlexvenueno aff
Huawang Qin, Yuewei Dai, Zhiquan Wang

Bibliographic record

VenueComputer and Information Science · 2009
Typearticle
Languageen
FieldComputer Science
TopicNetwork Security and Intrusion Detection
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceIntrusion toleranceIntrusionGame theoryNash equilibriumIntrusion detection systemComputer securityMathematical optimizationMathematical economicsMathematicsGeology

Abstract

fetched live from OpenAlex

Intrusion tolerance is the rising third generation technology of network security. For the shortcomings of existing models, a model of intrusion tolerant system based on game theory is proposed. The intrusion tolerant system and the intruder are seen as the two sides of the game. The income functions of the two sides are designed basing on some given concepts. Through quantifying and analyzing the income functions, the optimum strategies of the intrusion tolerant system and the intruder are obtained, and the Nash equilibrium of the game system is achieved finally. The results of analysis show that, this proposed model of intrusion tolerant system is consistent with the practical system.

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.

How this classification was reachedexpand

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.000
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 head0.011
GPT teacher head0.214
Teacher spread0.203 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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