Who you gonna call?: analyzing web requests in Android applications

M. Rapoport, Philippe Suter, Erik Wittern, O. Lhoták, Julian T Dolby
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引用次数: 17

Abstract

Relying on ubiquitous Internet connectivity, applications on mobile devices frequently perform web requests during their execution. They fetch data for users to interact with, invoke remote functionalities, or send user-generated content or meta-data. These requests collectively reveal common practices of mobile application development, like what external services are used and how, and they point to possible negative effects like security and privacy violations, or impacts on battery life. In this paper, we assess different ways to analyze what web requests Android applications make. We start by presenting dynamic data collected from running 20 randomly selected Android applications and observing their network activity. Next, we present a static analysis tool, Stringoid, that analyzes string concatenations in Android applications to estimate constructed URL strings. Using Stringoid, we extract URLs from 30, 000 Android applications, and compare the performance with a simpler constant extraction analysis. Finally, we present a discussion of the advantages and limitations of dynamic and static analyses when extracting URLs, as we compare the data extracted by Stringoid from the same 20 applications with the dynamically collected data.
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你要打给谁?:分析Android应用程序中的web请求
依靠无处不在的互联网连接,移动设备上的应用程序在执行过程中经常执行web请求。它们获取数据供用户交互、调用远程功能或发送用户生成的内容或元数据。这些请求共同揭示了移动应用开发的常见做法,如使用什么外部服务以及如何使用,它们指出了可能的负面影响,如安全和隐私侵犯,或对电池寿命的影响。在本文中,我们评估了分析Android应用程序发出的web请求的不同方法。我们首先展示从运行20个随机选择的Android应用程序并观察其网络活动中收集的动态数据。接下来,我们介绍了一个静态分析工具,Stringoid,它分析Android应用程序中的字符串连接,以估计构造的URL字符串。使用Stringoid,我们从30,000个Android应用程序中提取url,并将其性能与更简单的常量提取分析进行比较。最后,我们比较了Stringoid从相同的20个应用程序中提取的数据和动态收集的数据,讨论了动态和静态分析在提取url时的优点和局限性。
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MSR '20: 17th International Conference on Mining Software Repositories, Seoul, Republic of Korea, 29-30 June, 2020 Who you gonna call?: analyzing web requests in Android applications Cena słońca w projektowaniu architektonicznym Multi-extract and Multi-level Dataset of Mozilla Issue Tracking History Interactive Exploration of Developer Interaction Traces using a Hidden Markov Model
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