访问控制中的粒度面板

Ian Molloy, Mahesh V. Tripunitara, V. Lotz, M. Kuhlmann, C. Schaufler, V. Atluri
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引用次数: 1

摘要

这个小组将讨论以下问题。访问控制系统粒度的增加是否会产生可测量的风险降低并帮助实现组织的目标,或者成本是否过高?经过几十年的访问控制研究、产品和实践,已经出现了更复杂的访问控制策略和模型的趋势,这些策略和模型可以更精细地限制(或允许)对资源的访问。这允许策略管理员更紧密地指定他们可能想到的任何高级抽象策略,或者准确地执行诸如HIPPA、SOX或PCI之类的法规。最终目标是只允许那些事后想要的操作,或者通过Bishop等人称为Oracle Policy的方法。由于访问控制模型的表达能力各不相同,管理员可能需要更强大的模型来指定特定应用程序所需的高级策略。对于新模型来说,添加新的键属性、数据源、特性或关系以提供更丰富的工具集是很常见的。这导致了文献中新的一次性模型的爆炸式增长,其中很少有能够用于实际产品或部署。为了增强模型的表达能力、增加模型的粒度、降低管理的复杂性以及回答所需的安全性查询(如安全性),访问控制模型中添加了大量的新概念。举几个例子:群体和角色;层次结构和约束;参数化的权限;异常;用户和资源的时间和地点;主体之间的关系;主体、客体和动作的属性;信息流动;利益冲突阶层;义务;信任、利益和风险;工作流;代表团;态势感知和情境;等等......正如Barker所观察到的那样,所有这些构造都构建成一个元模型。这种粒度导致了许多新颖和有用的发现、新算法和具有挑战性的开放研究问题,但也带来了潜在的问题。粒度通常会带来复杂性,这体现在指定策略、管理和维护策略以及审计日志以确保遵从性方面。这个小组将讨论访问控制的复杂性问题。从设计和指定新模型,设计实际系统上的执行机制,策略生命周期,以及分析的角色,从自动生成策略到审计日志。那么,这种复杂性值得吗?增加粒度是否会降低敏感资源的风险并保护组织的目标,还是成本过高?我们能否真正指定一个“正确”和“完整”的政策,这可能过于动态,需要法院的解释来决定,特别是当政策旨在执行模棱两可的法规时。最后,我们应该以什么样的代价来争取一个完美的、细粒度的政策?是否应该将更多的资源用于从安全漏洞中恢复而不是预防?我们应该“让平均修复时间等于零,而不是让平均故障间隔时间等于无限”吗?
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Panel on granularity in access control
This panel will address the following question. Does an increase in the granularity of access control systems produce a measurable reduction in risk and help meet the goals of the organization, or is the cost prohibitively high? After decades of access control research, products, and practice, there has been a trend towards more complex access control policies and models that more finely restrict (or allow) access to resources. This allows policy administrators to more closely specify any high level abstract policy they may have in mind, or accurately enforce regulations such as HIPPA, SOX, or PCI. The end goal is to allow only those actions that are desirable in hindsight, or via an approach to which Bishop et al. refer as the Oracle Policy. As the expressive power of access control models can vary, an administrator may need a more powerful model to specify the high level policy they need for their particular application. It is not uncommon for new models to add new key-attributes, data-sources, features, or relations to provide a richer set of tools. This has resulted in an explosion of new one-off models in the literature, few of which make their way to real products or deployment. To increase the expressive power of a model, increase its granularity, reduce the complexity of administration and to answer desirable security queries such as safety, a plethora of new concepts have been added to access control models. To name a few: groups and roles; hierarchies and constraints; parameterized permissions; exceptions; time and location of users and resources; relationships between subjects; attributes of subjects, objects, and actions; information flow; conflict of interest classes; obligations; trust, benefit, and risk; workflows; delegation; situational awareness and context; and so on. All of these constructs build to a meta-model, as Barker observes. This granularity has resulted in many novel and useful findings, new algorithms, and challenging open research issues, but poses potential problems as well. With granularity often comes complexity which manifests itself in specifying policies, managing and maintaining policies over time, and auditing logs to ensure compliance. This panel will discuss issues surrounding the problem of complexity in access control. From designing and specifying new models, designing enforcement mechanisms on real-world systems, policy lifecycle, and the role of analytics from automatically generating policies to auditing logs. So, is this complexity worth it? Does increasing the granularity produce a measurable reduction in the risk to sensitive resources and protect the goals of the organization or is the cost prohibitively high? Can we ever truly specify a "correct" and "complete" policy, which may be too dynamic and require the interpretation of the courts to decide, especially when policies are intended to enforce ambiguous regulations. Finally, at what cost should we strive for a perfect, fine-grained policy? Should more resources be places on recovery from security breaches than on prevention? Should we be "going for mean time to repair equals zero rather than mean time between failure equals infinity."
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