A novel approach to role-based access control

Authors:
Song-hwa Chae;Wonil Kim;Dong-kyoo Kim
Affiliations:
The Graduate School of Information and Communication, Ajou University, Suwon, Republic of Korea;The Graduate School of Information and Communication, Ajou University, Suwon, Republic of Korea;College of Information and Computer Engineering, Ajou University, Suwon, Republic of Korea
Venue:
ICCS'03 Proceedings of the 2003 international conference on Computational science
Year:
2003

Citing 4
Cited 1

Elements of artificial neural networks

Elements of artificial neural networks
A role-based access control model and reference implementation within a corporate intranet

ACM Transactions on Information and System Security (TISSEC) - Special issue on role-based access control
Role-based authorization constraints specification

ACM Transactions on Information and System Security (TISSEC)
Proposed NIST standard for role-based access control

ACM Transactions on Information and System Security (TISSEC)

Role-Based access control model for ubiquitous computing environment

WISA'05 Proceedings of the 6th international conference on Information Security Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the rapid growth of distributed and network systems, sharing resources among many users become more common. As a result of that, we encounter with new problems concerning security and privacy on the shared resources. An access control mechanism such as role-based access control (RBAC) is one of the solutions to cope with these problems. RBAC is an efficient access control mechanism for organization data with role and permission management. In this paper, we propose a new implementation method for RBAC, which uses neural networks instead of tables. By employing neural network, it has advantages of not using multiple storages for rolepermission tables and extra mutual exclusive data tables. It also reduces access time for requested role and permission sets.