Role Mining with Missing Values

Vavilis, Sokratis; Egner, Alexandru; Petković, Milan; Zannone, Nicola

doi:10.1109/ares.2016.32

Cited by 5 publications

(6 citation statements)

References 26 publications

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“…Learning generative models from logs [49] and missing value tolerant variants of matrix factorization such as Multiple Factor Optimization (MFO) [44] have both been shown to be effective at handling incomplete activity records, and both approaches should be investigated. More generally, formalizing the contributions of different sources of overrides could lead to the development of a more nuanced and configurable unnecessary privilege metric, analogous to W SC.…”

Section: Resultsmentioning

confidence: 99%

“…However, the mechanism is agnostic to the origin of the overrides, and more advanced techniques could be applied as well or instead. In particular, learning generative models from logs [49] and missing value tolerant variants of matrix factorization such as Multiple Factor Optimization (MFO) [44] have both been shown to be effective at handling incomplete activity records, and their results could be applied as overrides.…”

Section: Privilege Assignment Overridesmentioning

confidence: 99%

See 1 more Smart Citation

Informed Privilege-Complexity Trade-Offs in RBAC Configuration

Currey¹,

McKinstry²,

Dadgar³

et al. 2020

Proceedings of the 25th ACM Symposium on Access Control Models and Technologies

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Role-Based Access Control (RBAC) has the potential both to simplify administration and improve an organization's security. But for non-trivial configurations, there is a conflict between defining fine-grained roles which adhere to the principle of least privilege, and coarse-grained roles which simplify administration by reducing configuration complexity. In this paper we propose OnPar, a multi-objective role mining approach which introduces minimization of unnecessary privilege as a role mining objective, along with an associated unnecessary privilege metric. These allow an RBAC configuration's level of adherence to the principle of least privilege to be reasoned about and traded off against other objectives, including minimization of configuration complexity. A key feature of our approach is the elimination of user tuning of global optimization weights. We show experimentally that this tuning typically leads to the evaluation of sub-optimal candidates, while still missing many optimal candidates. To avoid these issues we leverage Pareto optimality and introduce multi-stage Pareto filtering and the hypervolume indicator to role mining. Their use allows OnPar to efficiently select a small set of candidates for evaluation by the administrator, which are equal best and representative of the full range of trade-offs that were found. Our experimental results demonstrate the effectiveness of this approach across a wide range of input configurations. CCS CONCEPTS • Security and privacy → Information accountability and usage control; Access control; • Information systems → Data mining.

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Section: Resultsmentioning

confidence: 99%

Section: Privilege Assignment Overridesmentioning

confidence: 99%

Informed Privilege-Complexity Trade-Offs in RBAC Configuration

Currey¹,

McKinstry²,

Dadgar³

et al. 2020

Proceedings of the 25th ACM Symposium on Access Control Models and Technologies

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show abstract

“…It can eliminate inappropriate edges and improved the quality of generated roles. Vavilis et al [28] studied the minimal noise role mining problem and the multiple factor optimization role mining problem to mine roles from access control logs with noise information.…”

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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“…Many researchers have emphasized on the importance of this stage [12][13] particularly to generate a clean and quality data and usually pre-processing stage involve the process to clean the noises that might affect the results.…”

Section: Pre-processingmentioning

confidence: 99%

“…Assumed a set of users (U), a set of permissions (P) and a user-permission assignment (UPA) is given, acquire a set of roles (R), a user-role assignment (UA) and a role-permission assignment (PA) while reducing the number of roles |R| = k. In matrix notation, it can be formulated as [12]:…”

Section: Definition 3 (Basic Rmp)mentioning

confidence: 99%

A Conceptual Model of Role Based Access Control Using Role Mining Algorithm

Hamid¹,

Ahmad²,

Selamat³

2018

IJEECS

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Numerous studies have shown that currently, role-based access control has becoming one of the successful access control model because of its principle that could simplifies the work of security administrators. However, to construct a concise, role-based access control system, a good role mining algorithm structure is needed therefore the objectives of this paper are firstly, to provide a general overview on phases that involved in designing and developing the algorithm and secondly, to introduce a conceptual model that constructed based on the analysis and this model represents a general process in role mining model. This model involved series of phases that begin with the input of data, pre-processing stage, candidate role generation phase, role selection and role assignment process and lastly number of roles as generated output.

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Role Mining with Missing Values

Cited by 5 publications

References 26 publications

Informed Privilege-Complexity Trade-Offs in RBAC Configuration

Informed Privilege-Complexity Trade-Offs in RBAC Configuration

Access Control Role Evolution Mechanism for Open Computing Environment

A Conceptual Model of Role Based Access Control Using Role Mining Algorithm

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