基于烟尘的Android应用分析工具链

Steven Arzt, Siegfried Rasthofer, E. Bodden
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引用次数: 19

摘要

由于始终在线的移动设备处理大量高度敏感的信息所带来的质量和安全要求,Android应用程序是自动化程序分析的重要目标。然而,研究该领域的新方法通常需要将大量的工作花在与手头具体研究问题无关的工程任务上。这些编程和调试任务可能会大大延迟该领域的进展。因此,我们认为,该领域的研究极大地受益于拥有一个易于使用的组件和经过良好测试的基本算法的通用平台,研究人员可以在此基础上构建自己的原型。除了减少每项新研究所需的工程努力外,这样的平台还提供了一个在统一框架内比较不同方法的基础,从而促进了可比性和可重复性。在本文中,我们介绍了用于程序分析的Soot框架,以及构建在该框架之上的各种高度集成的开源工具和组件,这些工具和组件在设计时考虑到了可重用性。这些人工制品已经成为世界范围内许多研究和商业项目的核心。由于共享平台,来自一个工具的结果不仅可以用作其他工具的输入,而且单个数据对象可以传递,形成一个大的API,可以轻松地构建新的研究原型。
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The Soot-Based Toolchain for Analyzing Android Apps
Due to the quality and security requirements that come with an always-on mobile device processing large amounts of highly sensitive information, Android apps are an important target for automated program analysis. Yet, research on new approaches in this field often requires a significant amount of work to be spent on engineering tasks that are not central to the concrete research question at hand. These programming and debugging tasks can significantly delay the progress of the field. We therefore argue that research in the field greatly benefits from having a universal platform of readily usable components and well-tested fundamental algorithms on top of which researchers can build their own prototypes. Besides decreasing the required engineering effort for each new piece of research, such a platform also provides a base for comparing different approaches within one uniform framework, thereby fostering comparability and reproducibility. In this paper, we present the Soot framework for program analysis and various highly integrated open-source tools and components built on top of it that were designed with re-usability in mind. These artifacts are already at the core of many research and commercial projects worldwide. Due to the shared platform, results from one tool can not only be used as inputs for the others, but individual data objects can be passed around to form one large API with which one can build new research prototypes with ease.
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