Mining Relationship-Based Access Control Policies

Abstract

Relationship-based access control (ReBAC) provides a high level of expressiveness and flexibility that promotes security and information sharing. We formulate ReBAC as an object-oriented extension of attribute-based access control (ABAC) in which relationships are expressed using fields that refer to other objects, and path expressions are used to follow chains of relationships between objects. ReBAC policy mining algorithms have potential to significantly reduce the cost of migration from legacy access control systems to ReBAC, by partially automating the development of a ReBAC policy from an existing access control policy and attribute data. This paper presents an algorithm for mining ReBAC policies from access control lists (ACLs) and attribute data represented as an object model, and an evaluation of the algorithm on four sample policies and two large case studies. Our algorithm can be adapted to mine ReBAC policies from access logs and object models. It is the first algorithm for these problems.