Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
139 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Attribute Based Administration of Role Based Access Control : A Detailed Description (1706.03171v2)

Published 10 Jun 2017 in cs.CR

Abstract: Administrative Role Based Access Control (ARBAC) models deal with how to manage user-role assignments (URA), permission-role assignments (PRA), and role-role assignments (RRA). A wide variety of approaches has been proposed in the literature for URA, PRA, and RRA. In this paper, we propose attribute-based administrative models that unify many prior approaches for URA and PRA. The motivating factor is that attributes of various RBAC entities such as admin users, regular users and permissions can be used to administer URA and PRA in a highly flexible manner. We develop an attribute-based URA model called AURA and an attribute-based PRA model called ARPA. We demonstrate that AURA and ARPA can express and unify many prior URA and PRA models.

Citations (7)

Summary

We haven't generated a summary for this paper yet.