Towards an Efficient Policy Evaluation Process in Multi-Tenancy Cloud Environments

Meryeme Ayache, M. Erradi, Bernd Freisleben, A. Khoumsi
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引用次数: 1

Abstract

Cloud computing offers most of its services under multi-tenancy environments. To satisfy security requirements among collaborating tenants, each tenant may define a set of access control policies to secure access to shared data. Several cloud solutions make use of XACML to specify such policies. However, existing implementations of XACML perform a brute force search to compare a request to all existing rules in a given XACML policy. This decreases the decision process (i.e., policy evaluation) performance especially for policies with a large number of rules. In this paper, we propose an automata-based approach for an efficient XACML policy evaluation. We implemented our approach in a cloud policy engine called X2Automata. The engine first converts both XACML policies and access requests to automata. Second, it combines the two automata by a synchronous product. Third, it applies an evaluation procedure to the resulting automaton to decide whether an access request is granted or not. To highlight the efficiency of X2Automata, we compare its performance, based on the OpenStack cloud environment, with the XACML implementation named Balana.
面向多租户云环境的高效策略评估流程
云计算在多租户环境下提供大多数服务。为了满足协作租户之间的安全需求,每个租户可以定义一组访问控制策略来保护对共享数据的访问。一些云解决方案使用XACML来指定这些策略。但是,现有的XACML实现执行蛮力搜索,将请求与给定XACML策略中的所有现有规则进行比较。这降低了决策过程(即策略评估)的性能,特别是对于具有大量规则的策略。在本文中,我们提出了一种基于自动机的高效XACML策略评估方法。我们在名为X2Automata的云策略引擎中实现了我们的方法。该引擎首先将XACML策略和访问请求转换为自动机。其次,它通过一个同步产品将两个自动机结合起来。第三,它将评估过程应用于生成的自动化,以决定是否授予访问请求。为了突出X2Automata的效率,我们将其基于OpenStack云环境的性能与名为Balana的XACML实现进行了比较。
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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