策略不可知程序的分面执行

Thomas H. Austin, Jean Yang, C. Flanagan, Armando Solar-Lezama
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引用次数: 63

摘要

对于应用程序来说,保护敏感数据非常重要。即使对于简单的机密性和完整性策略,程序员通常也很难推断出策略应该如何交互以及如何在整个程序中执行策略。一种很有前途的方法是策略不可知编程,这种模型允许程序员将策略与核心功能分开实现。Yang等人描述了Jeeves,这是一种支持信息流策略的编程语言,它描述了如何在不同的输出通道中显示敏感值。Jeeves使用符号求值和约束求解来生成符合策略的输出。该策略提供了强大的机密性保证,但限制了表达性和实现可行性。我们用分面值扩展Jeeves,它利用敏感值的结构来产生更强的表达能力,并促进对运行时行为的推理。我们提出了Jeeves的面形语义,并描述了一个通过程序传播敏感信息的多个视图的模型。我们提供了对终止不敏感的不干扰的证明,并描述了语义如何促进对程序行为的推理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Faceted execution of policy-agnostic programs
It is important for applications to protect sensitive data. Even for simple confidentiality and integrity policies, it is often difficult for programmers to reason about how the policies should interact and how to enforce policies across the program. A promising approach is policy-agnostic programming, a model that allows the programmer to implement policies separately from core functionality. Yang et al. describe Jeeves, a programming language that supports information flow policies describing how to reveal sensitive values in different output channels. Jeeves uses symbolic evaluation and constraint-solving to produce outputs adhering to the policies. This strategy provides strong confidentiality guarantees but limits expressiveness and implementation feasibility. We extend Jeeves with faceted values, which exploit the structure of sensitive values to yield both greater expressiveness and to facilitate reasoning about runtime behavior. We present a faceted semantics for Jeeves and describe a model for propagating multiple views of sensitive information through a program. We provide a proof of termination-insensitive non-interference and describe how the semantics facilitate reasoning about program behavior.
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