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Record W2023463827 · doi:10.1142/s0218194003001317

Adding Flexibility in Information Flow Control for Object-Oriented Systems Using Versions

2003· article· en· W2023463827 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 Software Engineering and Knowledge Engineering · 2003
Typearticle
Languageen
FieldComputer Science
TopicSecurity and Verification in Computing
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsComputer scienceInformation flowFlexibility (engineering)Object (grammar)Process (computing)Distributed computingBlocking (statistics)ConfidentialityControl (management)EnforcementCloning (programming)Computer securityComputer networkProgramming languageArtificial intelligence

Abstract

fetched live from OpenAlex

One of the main features of information flow control is to ensure the enforcement of privacy and regulated accessibility. However, most information flow models that have been proposed do not provide substantial assurance to enforce end-to-end confidentiality policies or they are too restrictive, overprotected, and inflexible. This paper presents an approach to control flow information in object-oriented systems using versions, thus allowing considerable flexibility without compromising system security by leaking sensitive information. Models based on message filtering intercept every message exchanged among objects to control the flow of information. Versions are proposed to provide flexibility and avoid unnecessary and undesirable blocking of messages during the filtering process. Two options of operations are supported by versions — cloning reply and non-cloning reply. Furthermore, we present an algorithm which enforces message filtering through these operations.

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)0.001
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.014
GPT teacher head0.251
Teacher spread0.237 · 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