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海报:利用基尼不纯度挖掘带有环境属性的基于属性的访问控制策略

Poster: Using Gini Impurity to Mine Attribute-based Access Control Policies with Environment Attributes.

作者信息

Das Saptarshi, Sural Shamik, Vaidya Jaideep, Atluri Vijayalakshmi

机构信息

IIT Kharagpur, India.

Rutgers University, USA.

出版信息

Proc ACM Symp Access Control Model Technol. 2018 Jun;2018:213-215. doi: 10.1145/3205977.3208949.

Abstract

In Attribute-based Access Control (ABAC) systems, utilizing environment attributes along with the subject and object attributes introduces a dynamic nature to the access decisions. The inclusion of environment attributes helps in achieving a more fine-grained access control. In this paper, we present an ABAC policy mining algorithm that considers the environment attributes and their associated values while forming the rules. Furthermore, we use gini impurity to form the rules. This helps to minimize the number of rules in the generated policy. The experimental evaluation shows that our approach is quite effective in practice.

摘要

在基于属性的访问控制(ABAC)系统中,将环境属性与主体和客体属性一起使用,为访问决策引入了动态特性。环境属性的纳入有助于实现更细粒度的访问控制。在本文中,我们提出了一种ABAC策略挖掘算法,该算法在形成规则时会考虑环境属性及其相关值。此外,我们使用基尼不纯度来形成规则。这有助于最小化生成策略中的规则数量。实验评估表明,我们的方法在实践中相当有效。

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本文引用的文献

1
Efficient bottom-up Mining of Attribute Based Access Control Policies.
IEEE Conf Collab Internet Comput. 2017 Oct;2017:339-348. doi: 10.1109/CIC.2017.00051. Epub 2017 Dec 14.

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