Paper Info
Title
Role-Engineering Optimization With Cardinality Constraints And User-Oriented Mutually Exclusive Constraints
Abstract
Role-based access control (RBAC) is one of the most popular access-control mechanisms because of its convenience for management and various security policies, such as cardinality constraints, mutually exclusive constraints, and user-capability constraints. Role-engineering technology is an effective method to construct RBAC systems. However, mining scales are very large, and there are redundancies in the mining results. Furthermore, conventional role-engineering methods not only do not consider more than one cardinality constraint, but also cannot ensure authorization security. To address these issues, this paper proposes a novel method called role-engineering optimization with cardinality constraints and user-oriented mutually exclusive constraints (REO_CCUMEC). First, we convert the basic role mining into a clustering problem, based on the similarities between users and use-partitioning and compression technologies, in order to eliminate redundancies, while maintaining its usability for mining roles. Second, we present three role-optimization problems and the corresponding algorithms for satisfying single or double cardinality constraints. Third, in order to evaluate the performance of authorizations in a role-engineering system, the maximal role assignments are implemented, while satisfying multiple security constraints. The theoretical analyses and experiments demonstrate the accuracy, effectiveness, and efficiency of the proposed method.
Year
DOI
Venue
2019
10.3390/info10110342
INFORMATION
Keywords
Field
DocType
role engineering, role mining, role assignments, cardinality constraints, user-oriented mutually exclusive constraints
Data mining,Effective method,Computer science,Usability,Cardinality,Role-based access control,Theoretical computer science,Access control,Security policy,Cluster analysis,Mutually exclusive events
Journal
Volume
Issue
Citations 
10
11
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Wei Sun100.68
Hui Su200.68
Hongbing Liu3598.74