Role Minimization Optimization Algorithm Based on Concept Lattice Factor

Abstract

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.