The DOI matches its Crossref record.
The ARBAC97 model for role-based administration of roles
Open accessAbstract
In role-based access control (RBAC), permissions are associated with roles' and users are made members of roles, thereby acquiring the roles; permissions. RBAC's motivation is to simplify administration of authorizations. An appealing possibility is to use RBAC itself to manage RBAC, to further provide administrative convenience and scalability, especially in decentralizing administrative authority, responsibility, and chores. This paper describes the motivation, intuition, and formal definition of a new role-based model for RBAC administration. This model is called ARBAC97 (administrative RBAC '97) and has three components: URA97 (user-role assignment '97), RPA97 (permission-role assignment '97), and RRA97 (role-role assignment '97) dealing with different aspects of RBAC administration. URA97, PRA97, and an outline of RRA97 were defined in 1997, hence the designation given to the entire model. RRA97 was completed in 1998. ARBAC97 is described completely in this paper for the first time. We also discusses possible extensions of ARBAC97.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The NIST model for role-based access control: towards a unified standard
Sandhu, R., Ferraiolo, D., & Kuhn, R. (2000) · Proceedings of the fifth ACM workshop on Role-based access control · doi:10.1145/344287.344301 · Cited by 877
Self-citationSTORK: a real, heterogeneous, large-scale eID management system
Ribeiro, C., Leitold, H., Esposito, S., & Mitzam, D. (2018) · International Journal of Information Security · doi:10.1007/s10207-017-0385-x · Cited by 24
Metadata
- Authors
- Sandhu, R., Bhamidipati, V., & Munawer, Q.
- Venue
- ACM Transactions on Information and System Security
- Published
- 1999-02
- Volume
- 2
- Issue
- 1
- Pages
- 105-135
- ISSN
- 1094-9224 (ISSN-L)
- 1557-7406
- OpenAlex
- W1997862012
- Cited by
- 605
- References
- 0
- FWCI
- 66.93
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The ARBAC97 model for role-based administration of roles. https://app.cochat.ai/papers/10.1145/300830.300839
- The paper
- Sandhu, R., Bhamidipati, V., & Munawer, Q. (1999). The ARBAC97 model for role-based administration of roles. ACM Transactions on Information and System Security. https://doi.org/10.1145/300830.300839
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
