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Record W1574130501 · doi:10.5539/mas.v9n8p213

Mills Model Based Evaluation of Security of Software Systems

2015· article· en· W1574130501 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldComputer Science
TopicSoftware Reliability and Analysis Research
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceVulnerability (computing)Division (mathematics)Context (archaeology)Software security assuranceReliability (semiconductor)SoftwareProcess (computing)Software systemSecure codingComputer securityReliability engineeringSoftware engineeringInformation securitySecurity serviceOperating systemEngineering

Abstract

fetched live from OpenAlex

The presented paper discusses a possibility for an implementation of software reliability models for an evaluation of security of software. Mills model is proposed as the most suitable one. In order to use it more effectively it is proposed to implement a division of vulnerabilities into groups. Classification of vulnerabilities based on a method of their connection with features of a process's execution on a level of interaction of system resources and operating system is presented. Security of system in a context of a specific application can be evaluated more precisely by means of assigning of a certain weight to each group of vulnerabilities. The suggestions on an evaluation of vulnerability of software taking into account a division of vulnerabilities into groups according to the presented classification are made.

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)0.008
metaresearch head score (Gemma)0.001
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 score0.861
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.067
GPT teacher head0.341
Teacher spread0.274 · 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