Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review

Ahmad, Rabiah and Abd Hamid, Nazirah and Selamat, Siti Rahayu (2018) Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review. International Journal Of Engineering & Technology, 7. 306-310 . ISSN 2227-524X

[img] Text
IJET-23386.pdf - Published Version

Download (393kB)

Abstract

A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles.

Item Type: Article
Uncontrolled Keywords: Access Control; Information Security; Optimization Metric; RBAC; Role Mining
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Faculty of Information and Communication Technology
Depositing User: Mohd. Nazir Taib
Date Deposited: 08 Jul 2019 04:53
Last Modified: 30 Aug 2021 13:36
URI: http://eprints.utem.edu.my/id/eprint/23016
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item