RanSAM: Randomized Search for ABAC Policy Mining

Nakul Aggarwal, S. Sural
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引用次数: 1

Abstract

This paper presents a novel approach for generating Attribute-based Access Control policies from a given Access Control Matrix (ACM). In contrast to the existing techniques for policy mining, which group the desired accesses in the ACM using certain heuristics, we pose it as a search problem in the policy space. A randomized algorithm is then used to identify the policy that best represents the given ACM. Our initial experiments show promising results.
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RanSAM: ABAC策略挖掘的随机搜索
本文提出了一种从给定的访问控制矩阵(ACM)生成基于属性的访问控制策略的新方法。现有的策略挖掘技术使用某些启发式方法对ACM中的期望访问进行分组,与之相反,我们将其视为策略空间中的搜索问题。然后使用随机算法来确定最能代表给定ACM的策略。我们的初步实验显示出有希望的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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