定量动态数据流跟踪

CODASPY : proceedings of the ... ACM conference on data and application security and privacy. ACM Conference on Data and Application Security & Privacy Pub Date : 2014-03-03 DOI:10.1145/2557547.2557551

Enrico Lovat, Johan Oudinet, A. Pretschner

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引用次数: 12

摘要

提出了一种用于动态定量数据流跟踪的非概率模型。在运行时对特定表示形式(文件、窗口、网络数据包)中存储的数据量进行估计，可以采用细粒度策略来授权或禁止部分数据泄漏。我们证明了估计的正确性，提供了一个评估w.r.t.精度和性能的实现，并在操作系统级别分析了一个实例。

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On quantitative dynamic data flow tracking

We present a non-probabilistic model for dynamic quantitative data flow tracking. Estimations of the amount of data stored in a particular representation at runtime - a file, a window, a network packet - enable the adoption of fine-grained policies which authorize or prohibit partial leaks of data. We prove the correctness of the estimations, provide an implementation that we evaluate w.r.t. precision and performance, and analyze one instantiation at the OS level.

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CODASPY : proceedings of the ... ACM conference on data and application security and privacy. ACM Conference on Data and Application Security & Privacy

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