Mining temporal roles using many-valued concepts

Mitra, Barsha; Sural, Shamik; Vaidya, Jaideep; Atluri, Vijayalakshmi

doi:10.1016/j.cose.2016.04.002

Cited by 18 publications

(30 citation statements)

References 38 publications

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“…Bertino et al allow the REB to specify various conditions and events that enabled or disable a role. Like Mitra et al [8,9], we are interested only in temporal conditions and therefore consider a limited form of REB, which we call a role-time assignment. Specifically, a role-time assignment TA maps each role to a BPES.…”

Section: Background On Trbacmentioning

confidence: 99%

“…Mitra et al developed another temporal role mining algorithm, called the CO-TRAPMP-MVCL algorithm [9]. It minimizes a restricted variant of WSC based on the sizes of two components of the policy.…”

Section: Introductionmentioning

confidence: 99%

“…This paper is a revised and extended version of [12]. The main improvements are substitution of FastMiner for CompleteMiner when computing role intersections and an empirical justification for this, an improved metric for selecting a subset of initial roles for use in role intersections, more explanation and details of the algorithm, and more experiments, including an experimental comparison with Mitra et al's CO-TRAPMP-MVCL algorithm [9].…”

Section: Introductionmentioning

confidence: 99%

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Mining hierarchical temporal roles with multiple metrics

Stoller

Bui

2017

JCS

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Temporal role-based access control (TRBAC) extends role-based access control to limit the times at which roles are enabled. This paper presents a new algorithm for mining high-quality TRBAC policies from timed ACLs (i.e., ACLs with time limits in the entries) and optionally user attribute information. Such algorithms have potential to significantly reduce the cost of migration from timed ACLs to TRBAC. The algorithm is parameterized by the policy quality metric. We consider multiple quality metrics, including number of roles, weighted structural complexity (a generalization of policy size), and (when user attribute information is available) interpretability, i.e., how well role membership can be characterized in terms of user attributes. Ours is the first TRBAC policy mining algorithm that produces hierarchical policies, and the first that optimizes weighted structural complexity or interpretability. In experiments with datasets based on real-world ACL policies, our algorithm is more effective than previous algorithms at optimizing policy quality.

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Section: Background On Trbacmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mining hierarchical temporal roles with multiple metrics

Stoller

Bui

2017

JCS

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“…Since role mining was proposed, 6 it has been used to generate roles according to different optimization objectives, such as minimizing the number of generated roles or the weighted structure complexity, 12 satisfying various constraints such as separation of duty, least privilege, and temporal constraint, 13,14 and semantic meaning based on the information about the business process or the user attributes. 15,16 Hachana et al 17 formally defined the problem of role set comparison that is proved to be NP-complete and proposed a greedy algorithm to map inherent relations between the original set of roles and the mined set of roles based on algebraic expression, but the system must support the negation of roles, which are not satisfied by most systems.…”

Section: Related Workmentioning

confidence: 99%

“…Each iteration begins by sorting the candidate roles in descending order by the number of assignments they can cover (line 4), and the detail of procedure Sort(CR, UPA) is described in Algorithm 3. At the beginning of main loop when |GR| < |QR| (lines 5-20), for each candidate role (CR i ), the qualified role (QR ′ j ) with the maximum similarity (Sim(k)) is selected and calculate CR i 's Score, which is a deformation of the Objective Function (lines [11][12][13][14][15]. The candidate role with the maximum Score (BestScore) is added to GR (line 20) and flip the element 1 covered by it to 0 in the matrix UPA (line 24), the detail of which is described in Algorithm 4.…”

Section: Second Phasementioning

confidence: 99%

An efficiency approach for RBAC reconfiguration with minimal roles and perturbation

Pan

Zhu

Liangsheng

et al. 2017

Concurrency and Computation

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Summary Role‐based access control (RBAC) has been widely used based on its good applicability and high flexibility in recent years. However, the RBAC system needs to be updated to meet the changes in access control policies during its run time. As the complexity of modifying role‐permission assignments, new roles are continuously added to the system without considering the business processes and the user demands. Therefore, the RBAC system needs to be reconfigured over time to optimize the RBAC configuration and keep as close as possible to the original at the same time. Although there have several RBAC reconfiguration schemes by generating roles that are similar to the deployed ones, most of them neglect the difference between roles (meaningful or meaningless, frequently used, or infrequently used, etc) and generate more roles than needed, which in turn increases the system management burden. In this paper, we first propose a method to evaluate the quality of roles based on two indicators and formally define the problem of RBAC reconfiguration with minimal roles and perturbation. Then, we present a log‐based RBAC reconfiguration approach that handles the motivation problem and its detail algorithm process. The effectiveness and stability of our approach is demonstrated by experiments at last.

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