Toward edge minability for role mining in bipartite networks

Dong, Lijun; Wang, Yi; Ran, Lingkun; Pi, Benjie; Wu, Liuyi

doi:10.1016/j.physa.2016.06.068

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…Then it assigned roles based on similarity analysis between concept lattices. Dong et al [27] used bipartite networks to find roles, and proposed a method to evaluate the importance of edges in bipartite networks. It can eliminate inappropriate edges and improved the quality of generated roles.…”

Section: Related Workmentioning

confidence: 99%

Access Control Role Evolution Mechanism for Open Computing Environment

Liu

Wang

2020

Electronics

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Data resources in open computing environments (including big data, internet of things and cloud computing) are characterized by large scale, wide source, and strong dynamics. Therefore, the user-permission relationship of open computing environments has a huge scale and will be dynamically adjusted over time, which enables effective permission management in the role based access control (RBAC) model to become a challenging problem. In this paper, we design an evolution mechanism of access control roles for open computing environments. The mechanism utilizes the existing user-permission relationship in the current system to mine the access control role and generate the user-role and role-permission relationship. When the user-permission relationship changes, the roles are constantly tuned and evolved to provide role support for access control of open computing environments. We propose a novel genetic-based role evolution algorithm that can effectively mine and optimize roles while preserving the core permissions of the system. In addition, a role relationship aggregation algorithm is proposed to realize the clustering of roles, which provides a supplementary reference for the security administrator to give the role real semantic information. Experimental evaluations in real-world data sets show that the proposed mechanism is effective and reliable.

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Section: Related Workmentioning

confidence: 99%

Access Control Role Evolution Mechanism for Open Computing Environment

Liu

Wang

2020

Electronics

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“…Du X and Change X proposed two algorithms based on artificial intelligence, i.e., the genetic algorithm and ant colony optimization algorithm [18]. Dong et al proposed both fast exact and heuristic methods based on biclique network cover to minimize role number or edge number [19].…”

Section: Related Workmentioning

confidence: 99%

“…With regard to goodness measure, several metrics have been proposed in the literature, including minimizing the number of roles [10,20], minimizing the number of edges [13,14,19], minimizing the number of user-role assignment and permission-role assignment relations [13], minimizing both the number of roles and edges [21], and minimizing the administrative cost [22]. These optimization goals can be uniformly represented by the Weighted Structural Complexity (WSC) [8,9].…”

Section: Related Workmentioning

confidence: 99%

RMMDI: A Novel Framework for Role Mining Based on the Multi-Domain Information

Bai

Pan

Guo

et al. 2019

Security and Communication Networks

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Role-based access control (RBAC) is widely adopted in network security management, and role mining technology has been extensively used to automatically generate user roles from datasets in a bottom-up way. However, almost all role mining methods discover the user roles from existing user-permission assignments, which neglect the dependency relationships between user permissions. To extend the ability of role mining technology, this paper proposes a novel role mining framework based on multi-domain information. The framework estimates the similarity between different permissions based on the fundamental information in the physical, network, and digital domains and attaches interdependent permissions to the same role. Three simulated network scenarios with different multi-domain configurations are used to validate the effectiveness of our method. The experimental results show that the method can not only capture the interdependent relationships between permissions, but also detect user roles and permissions more reasonably.

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