Efficient purely-dynamic information flow analysis

Efficient purely-dynamic information flow analysis
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高效的纯动态信息流分析

DOI:
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发表时间:
2009
期刊:
SIGP
影响因子:
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通讯作者:
C. Flanagan
C. Flanagan
中科院分区:
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文献类型:
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作者:
Thomas H. Austin;C. Flanagan

文献摘要

被引文献

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我们提出了一种新颖的方法,可有效地以动态类型的语言(例如JavaScript)跟踪信息流。我们的方法纯粹是动态的,它通过动态检查检测到隐式路径的问题,该检查避免了进行近似静态分析的需求,同时仍保证了非干扰。我们将此检查纳入了一个基于稀疏信息标签的有效评估策略中,该标签会尽可能将信息流标签留置,并仅针对安全域之间迁移的值引入明确的标签。我们提出了实验结果,表明,在一系列小基准计划中,稀疏标签可为通用标签提供大量(30%-50%)的速度。
We present a novel approach for efficiently tracking information flow in a dynamically-typed language such as JavaScript. Our approach is purely dynamic, and it detects problems with implicit paths via a dynamic check that avoids the need for an approximate static analyses while still guaranteeing non-interference. We incorporate this check into an efficient evaluation strategy based on sparse information labeling that leaves information flow labels implicit whenever possible, and introduces explicit labels only for values that migrate between security domains. We present experimental results showing that, on a range of small benchmark programs, sparse labeling provides a substantial (30%-50%) speed-up over universal labeling.