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Record W2129728124 · doi:10.1109/wicsa.2001.948401

An object-oriented RBAC model for distributed system

2002· article· en· W2129728124 on OpenAlexaff
N.Z. Chang, Cungang Yang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicAccess Control and Trust
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsRole-based access controlComputer scienceAccess controlDistributed computingAuthorizationObject (grammar)ArchitectureDistributed objectDomain (mathematical analysis)Computer securityCommon Object Request Broker Architecture

Abstract

fetched live from OpenAlex

In distributed computing environments, users would like to share resources and communicate with each other to perform their jobs more efficiently. For better performance, it is important to keep resources and information integrity from unexpected use by unauthorized users. Therefore, there is a strong demand for access control of distributed shared resources. Role-Based-Access-Control (RBAC) has been introduced and offers a powerful means for specifying access control decisions. The authors propose an object oriented RBAC model for distributed system (ORBAC), it efficiently represents the real world. Moreover, under the decentralized ORBAC management architecture, an implementation of the model has realized multiple-domain access control. Finally, statically and dynamically role authorization is considered and a method to deal with the problem of separation of duties is presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0060.005
Open science0.0050.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0060.005

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 head0.033
GPT teacher head0.297
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations24
Published2002
Admission routes1
Has abstractyes

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