SmartDroid: an automatic system for revealing UI-based trigger conditions in android applications

Cong Zheng, Shixiong Zhu, Shuaifu Dai, G. Gu, Xiaorui Gong, Xinhui Han, Wei Zou
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引用次数: 264

Abstract

User interface (UI) interactions are essential to Android applications, as many Activities require UI interactions to be triggered. This kind of UI interactions could also help malicious apps to hide their sensitive behaviors (e.g., sending SMS or getting the user's device ID) from being detected by dynamic analysis tools such as TaintDroid, because simply running the app, but without proper UI interactions, will not lead to the exposure of sensitive behaviors. In this paper we focus on the challenging task of triggering a certain behavior through automated UI interactions. In particular, we propose a hybrid static and dynamic analysis method to reveal UI-based trigger conditions in Android applications. Our method first uses static analysis to extract expected activity switch paths by analyzing both Activity and Function Call Graphs, and then uses dynamic analysis to traverse each UI elements and explore the UI interaction paths towards the sensitive APIs. We implement a prototype system SmartDroid and show that it can automatically and efficiently detect the UI-based trigger conditions required to expose the sensitive behavior of several Android malwares, which otherwise cannot be detected with existing techniques such as TaintDroid.
SmartDroid:一种在android应用程序中显示基于ui的触发条件的自动系统
用户界面(UI)交互对Android应用程序至关重要,因为许多activity需要触发UI交互。这种UI交互还可以帮助恶意应用隐藏其敏感行为(例如,发送短信或获取用户的设备ID),以免被TaintDroid等动态分析工具检测到,因为简单地运行应用,但没有适当的UI交互,不会导致敏感行为的暴露。在本文中,我们关注通过自动化UI交互触发特定行为的挑战性任务。特别是,我们提出了一种静态和动态混合分析方法来揭示Android应用中基于ui的触发条件。我们的方法首先使用静态分析来通过分析活动和函数调用图来提取预期的活动切换路径,然后使用动态分析来遍历每个UI元素并探索通向敏感api的UI交互路径。我们实现了一个原型系统SmartDroid,并表明它可以自动有效地检测基于ui的触发条件,以暴露几个Android恶意软件的敏感行为,否则无法用现有的技术(如TaintDroid)检测到。
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