Identification and Attribution of Access Roles Using Hierarchical Team Permission Analysis

Iryna Didinova, Karel Macek, Karel Macek

2024

Abstract

This paper addresses the challenges of Role-Based Access Control (RBAC) in large organizations, with a focus on the efficient attribution of access roles. It critiques traditional role-mining algorithms and the use of Machine Learning (ML) models, which serve as benchmarks due to their lack of practical interpretability and potential security vulnerabilities. The novel contribution of this work is the introduction of the Hierarchical Team Permission Analysis (HTPA), a methodology grounded in organizational hierarchy. HTPA is shown to outperform the benchmark approaches by creating meaningful, interpretable roles that enhance both the security and efficiency of access control systems in large enterprises. The paper advocates for the potential integration of HTPA with ML models to further optimize role attribution and suggests avenues for future research in this evolving field.

Paper Citation

in Harvard Style

Didinova I. and Macek K. (2024). Identification and Attribution of Access Roles Using Hierarchical Team Permission Analysis. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 721-728. DOI: 10.5220/0012675300003690

in Bibtex Style

@conference{iceis24,
author={Iryna Didinova and Karel Macek},
title={Identification and Attribution of Access Roles Using Hierarchical Team Permission Analysis},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={721-728},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012675300003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Identification and Attribution of Access Roles Using Hierarchical Team Permission Analysis
SN - 978-989-758-692-7
AU - Didinova I.
AU - Macek K.
PY - 2024
SP - 721
EP - 728
DO - 10.5220/0012675300003690
PB - SciTePress