The RBAC model eases the administration of complex organizations and supports the implementation of basic security principles such as least privilege and separation of duty (SoD). In this work, we present PP-SSP, a Post-Processing Heuristic for the Static Separation of Permissions Problem. The heuristic has been designed to decouple role discovery from constraint enforcement phase, so that any existing rolemining algorithm can be selected at the beginning, making then the framework flexible and easily adaptable to different mining techniques. We evaluate the heuristic against a number of public datasets, report the results obtained, and discuss its performance in terms of different metrics, showing its efficiency and effectiveness.

A Post-Processing Heuristic for the Static Separation of Permissions Problem / C. Blundo, S.C. (PROCEEDINGS IEEE ANNUAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE WORKSHOPS). - In: COMPSAC 2026 / [a cura di] H. Shahriar, K. Shafiul Alam, H. Ohsaki, S. Cimato, M. Capretz, S. Ahmed, S. Iqbal Ahamed, AKM Jahangir Alam Majumder, M.l Haque, T. Yoshihisa, A. Cuzzocrea, Mi. Takemoto, N. Sakib, M. Elsayed. - [s.l] : Institute of Electrical and Electronics Engineers Inc., 2026. - ISBN 979-8-3315-4497-3. - pp. 2717-2722 (( 50. Annual Computers, Software, and Applications Conference : July, 7th - 10th Madrid 2026 [10.1109/compsac69091.2026.00408].

A Post-Processing Heuristic for the Static Separation of Permissions Problem

S. Cimato
Ultimo
2026

Abstract

The RBAC model eases the administration of complex organizations and supports the implementation of basic security principles such as least privilege and separation of duty (SoD). In this work, we present PP-SSP, a Post-Processing Heuristic for the Static Separation of Permissions Problem. The heuristic has been designed to decouple role discovery from constraint enforcement phase, so that any existing rolemining algorithm can be selected at the beginning, making then the framework flexible and easily adaptable to different mining techniques. We evaluate the heuristic against a number of public datasets, report the results obtained, and discuss its performance in terms of different metrics, showing its efficiency and effectiveness.
constrained role mining; heuristics; RBAC;
Settore INFO-01/A - Informatica
2026
Institute of Electrical and Electronics Engineers (IEEE)
Universidad Politecnica de Madrid
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1274703
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