熟练度的表达:访问控制策略规范自然语言的良性循环

P. Inglesant, M. Sasse, D. Chadwick, L. Shi
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引用次数: 47

摘要

在网格计算这个不断发展的领域中,实现可用的安全性尤其具有挑战性,因为在网格计算中,控制是分散的,系统是异构的,并且授权可以跨管理域应用。PERMIS基于基于角色的访问控制(RBAC)模型,提供了一个统一的基础设施来应对这些挑战。先前的研究发现,不了解PERMIS RBAC模型的资源所有者在表达访问控制策略方面存在困难。我们通过研究使用受控的自然语言解析器来表达这些策略,解决了这个问题。在本文中,我们描述了我们在PERMIS Editor的解析器的设计、实现和评估方面的经验。通过对45位网格实践者的访谈和焦点小组,我们首先了解了资源所有者表达的网格访问控制需求。我们发现网格计算使用的许多领域呈现出不同的安全需求;这意味着一个最小的,开放的设计。我们设计并实现了一个受控的自然语言系统来支持这些需求,我们对17个目标用户的横截面进行了评估。我们发现参与者并没有被文本编辑器吓倒,而且很容易理解语法。但是,对受控语言的一些严格要求是有问题的。使用受控的自然语言有助于克服PERMIS RBAC与旧范式之间的一些概念不匹配;然而,仍有一些微妙之处并不总是被理解。总之,解析器本身是不够的,应该在与PERMIS Editor的其他部分的相互作用中看到,这样,迭代地,帮助用户理解底层PERMIS模型,并更准确、更完整地表达他们的安全策略。
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Expressions of expertness: the virtuous circle of natural language for access control policy specification
The implementation of usable security is particularly challenging in the growing field of Grid computing, where control is decentralised, systems are heterogeneous, and authorization applies across administrative domains. PERMIS, based on the Role-Based Access Control (RBAC) model, provides a unified infrastructure to address these challenges. Previous research has found that resource owners who do not understand the PERMIS RBAC model have difficulty expressing access control policies. We have addressed this issue by investigating the use of a controlled natural language parser for expressing these policies. In this paper, we describe our experiences in the design, implementation, and evaluation of this parser for the PERMIS Editor. We began by understanding Grid access control needs as expressed by resource owners, through interviews and focus groups with 45 Grid practitioners. We found that the many areas of Grid computing use present varied security requirements; this suggests a minimal, open design. We designed and implemented a controlled natural language system to support these needs, which we evaluated with a cross-section of 17 target users. We found that participants were not daunted by the text editor, and understood the syntax easily. However, some strict requirements of the controlled language were problematic. Using controlled natural language helps overcome some conceptual mis-matches between PERMIS RBAC and older paradigms; however, there are still subtleties which are not always understood. In conclusion, the parser is not sufficient on its own, and should be seen in the interplay with other parts of the PERMIS Editor, so that, iteratively, users are helped to understand the underlying PERMIS model and to express their security policies more accurately and more completely.
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