信息流控制的类型:标记粒度和语义模型

Vineet Rajani, D. Garg
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引用次数: 23

摘要

基于语言的信息流控制(IFC)使用敏感标签跟踪程序中的依赖关系,并禁止公开输出依赖于秘密输入。特别是,文献已经提出了几个类型系统来跟踪这些依赖关系。在一个极端情况下,存在细粒度类型系统(如Flow Caml),它们单独标记所有值,并在单个值的级别上跟踪依赖关系。另一个极端是粗粒度类型系统(如HLIO),它通过将单个标签与整个计算上下文关联而不是单独标记所有值来粗略地跟踪依赖性。在本文中,我们表明,尽管这两种风格有明显的差异,但实际上,这两种风格都具有同样的表现力。为此,我们展示了从粗粒度类型系统到细粒度类型系统之间保持语义和类型的转换,反之亦然。向前转换并不令人惊讶,但向后转换则令人惊讶:它需要一个构造来任意限制粗粒度类型系统中上下文标签的范围(例如,HLIO的“toLabeled”构造)。作为一个单独的贡献,我们展示了如何将IFC类型的逻辑关系模型的工作扩展到高阶状态。我们为细粒度类型系统和粗粒度类型系统构建这样的逻辑关系。我们用这些关系来证明这两种类型系统以及它们之间的翻译是正确的。
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Types for Information Flow Control: Labeling Granularity and Semantic Models
Language-based information flow control (IFC) tracks dependencies within a program using sensitivity labels and prohibits public outputs from depending on secret inputs. In particular, literature has proposed several type systems for tracking these dependencies. On one extreme, there are fine-grained type systems (like Flow Caml) that label all values individually and track dependence at the level of individual values. On the other extreme are coarse-grained type systems (like HLIO) that track dependence coarsely, by associating a single label with an entire computation context and not labeling all values individually. In this paper, we show that, despite their glaring differences, both these styles are, in fact, equally expressive. To do this, we show a semantics- and type-preserving translation from a coarse-grained type system to a fine-grained one and vice-versa. The forward translation isn't surprising, but the backward translation is: It requires a construct to arbitrarily limit the scope of a context label in the coarse-grained type system (e.g., HLIO's ``toLabeled'' construct). As a separate contribution, we show how to extend work on logical relation models of IFC types to higher-order state. We build such logical relations for both the fine-grained type system and the coarse-grained type system. We use these relations to prove the two type systems and our translations between them sound.
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