Role Minimization Optimization Algorithm Based on Concept Lattice Factor

Role-based access control (RBAC) is a widely adopted security model that provides a flexible and scalable approach for managing permissions in various domains. One of the critical challenges in RBAC is the efficient assignment of roles to users while minimizing the number of roles involved. This art...

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Main Authors: Tao Wang, Qiang Wu
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/11/14/3047
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author Tao Wang
Qiang Wu
author_facet Tao Wang
Qiang Wu
author_sort Tao Wang
collection DOAJ
description Role-based access control (RBAC) is a widely adopted security model that provides a flexible and scalable approach for managing permissions in various domains. One of the critical challenges in RBAC is the efficient assignment of roles to users while minimizing the number of roles involved. This article presents a novel role minimization optimization algorithm (RMOA) based on the concept lattice factor to address this challenge. The proposed RMOA leverages the concept lattice, a mathematical structure derived from formal concept analysis, to model and analyze the relationships between roles, permissions, and users in an RBAC system. By representing the RBAC system as a concept lattice, the algorithm captures the inherent hierarchy and dependencies among roles and identifies the optimal role assignment configuration. The RMOA operates in two phases: the first phase focuses on constructing the concept lattice from the RBAC system’s role–permission–user relations, while the second phase performs an optimization process to minimize the number of roles required for the access control. It determines the concept lattice factor using the concept lattice interval to discover the minimum set of roles. The optimization process considers both the user–role assignments and the permission–role assignments, ensuring that access requirements are met while reducing role proliferation. Experimental evaluations conducted on diverse RBAC datasets demonstrate the effectiveness of the proposed algorithm. The RMOA achieves significant reductions in the number of roles compared to existing role minimization approaches, while preserving the required access permissions for users. The algorithm’s efficiency is also validated by its ability to handle large-scale RBAC systems within reasonable computational time.
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spelling doaj.art-dffd54d9eebf4e149cf3170b99b0ea032023-11-18T20:19:45ZengMDPI AGMathematics2227-73902023-07-011114304710.3390/math11143047Role Minimization Optimization Algorithm Based on Concept Lattice FactorTao Wang0Qiang Wu1Department of Computer Science and Technology, Shaoxing University, Shaoxing 312000, ChinaDepartment of Computer Science and Technology, Shaoxing University, Shaoxing 312000, ChinaRole-based access control (RBAC) is a widely adopted security model that provides a flexible and scalable approach for managing permissions in various domains. One of the critical challenges in RBAC is the efficient assignment of roles to users while minimizing the number of roles involved. This article presents a novel role minimization optimization algorithm (RMOA) based on the concept lattice factor to address this challenge. The proposed RMOA leverages the concept lattice, a mathematical structure derived from formal concept analysis, to model and analyze the relationships between roles, permissions, and users in an RBAC system. By representing the RBAC system as a concept lattice, the algorithm captures the inherent hierarchy and dependencies among roles and identifies the optimal role assignment configuration. The RMOA operates in two phases: the first phase focuses on constructing the concept lattice from the RBAC system’s role–permission–user relations, while the second phase performs an optimization process to minimize the number of roles required for the access control. It determines the concept lattice factor using the concept lattice interval to discover the minimum set of roles. The optimization process considers both the user–role assignments and the permission–role assignments, ensuring that access requirements are met while reducing role proliferation. Experimental evaluations conducted on diverse RBAC datasets demonstrate the effectiveness of the proposed algorithm. The RMOA achieves significant reductions in the number of roles compared to existing role minimization approaches, while preserving the required access permissions for users. The algorithm’s efficiency is also validated by its ability to handle large-scale RBAC systems within reasonable computational time.https://www.mdpi.com/2227-7390/11/14/3047role-based access control (RBAC)role minimizationintervalsconcept lattice factor
spellingShingle Tao Wang
Qiang Wu
Role Minimization Optimization Algorithm Based on Concept Lattice Factor
Mathematics
role-based access control (RBAC)
role minimization
intervals
concept lattice factor
title Role Minimization Optimization Algorithm Based on Concept Lattice Factor
title_full Role Minimization Optimization Algorithm Based on Concept Lattice Factor
title_fullStr Role Minimization Optimization Algorithm Based on Concept Lattice Factor
title_full_unstemmed Role Minimization Optimization Algorithm Based on Concept Lattice Factor
title_short Role Minimization Optimization Algorithm Based on Concept Lattice Factor
title_sort role minimization optimization algorithm based on concept lattice factor
topic role-based access control (RBAC)
role minimization
intervals
concept lattice factor
url https://www.mdpi.com/2227-7390/11/14/3047
work_keys_str_mv AT taowang roleminimizationoptimizationalgorithmbasedonconceptlatticefactor
AT qiangwu roleminimizationoptimizationalgorithmbasedonconceptlatticefactor