Android应用程序集的污染流分析

William Klieber, Lori Flynn, Amar Bhosale, Limin Jia, Lujo Bauer
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引用次数: 221

摘要

防御恶意Android应用程序的一种方法是分析它们以检测潜在的信息泄露。本文描述了一种新的Android静态污染分析,它结合并增强了FlowDroid和Epicc分析,以精确跟踪一组Android应用程序中的组件间和组件内数据流。分析分两个阶段进行:给定一组应用程序,我们首先确定每个应用程序单独启用的数据流,以及实现这些数据流的条件;然后,我们在这些结果的基础上,列举整个应用程序集支持的潜在危险数据流。本文介绍了我们的分析方法、实现和实验结果。
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Android taint flow analysis for app sets
One approach to defending against malicious Android applications has been to analyze them to detect potential information leaks. This paper describes a new static taint analysis for Android that combines and augments the FlowDroid and Epicc analyses to precisely track both inter-component and intra-component data flow in a set of Android applications. The analysis takes place in two phases: given a set of applications, we first determine the data flows enabled individually by each application, and the conditions under which these are possible; we then build on these results to enumerate the potentially dangerous data flows enabled by the set of applications as a whole. This paper describes our analysis method, implementation, and experimental results.
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Android taint flow analysis for app sets Large-scale configurable static analysis A software product line for static analyses: the OPAL framework Explicit and symbolic techniques for fast and scalable points-to analysis TS4J: a fluent interface for defining and computing typestate analyses
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