动态污点分析在android设备上防止隐私信息泄露的有效性研究

Golam Sarwar, O. Mehani, R. Boreli, M. Kâafar
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引用次数: 125

摘要

我们研究了使用动态污点分析来跟踪基于android的移动设备上的隐私敏感信息的局限性。当数据通过变量、进程间消息和文件传播时,污点跟踪通过标记污点标记来跟踪数据。一个流行的污点跟踪系统,TaintDroid,在Android移动应用程序中使用这种方法来标记私人信息,如设备标识符或用户的联系方式,并随后在这些信息被滥用时发出警告(例如,发送给不受欢迎的第三方)。我们展示了一系列基于android的污染跟踪攻击。具体来说,我们在移动设备环境中应用通用类的防污染方法来规避这种安全技术。我们已经在Android应用程序ScrubDroid中实现了所介绍的技术。我们成功地在Android OS 2.3到4.1.1版本的TaintDroid实现中测试了我们的应用,同时使用模拟器和真实设备。最后,我们评估了攻击的成功率和完成时间。我们得出的结论是,尽管污染跟踪可能是软件开发人员的一个有价值的工具,但它不能有效地保护敏感数据免受恶意攻击者的黑盒代码的攻击,这些攻击者使用任何提出的反污染跟踪方法。
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On the effectiveness of dynamic taint analysis for protecting against private information leaks on Android-based devices
We investigate the limitations of using dynamic taint analysis for tracking privacy-sensitive information on Android-based mobile devices. Taint tracking keeps track of data as it propagates through variables, interprocess messages and files, by tagging them with taint marks. A popular taint-tracking system, TaintDroid, uses this approach in Android mobile applications to mark private information, such as device identifiers or user's contacts details, and subsequently issue warnings when this information is misused (e.g., sent to an un-desired third party). We present a collection of attacks on Android-based taint tracking. Specifically, we apply generic classes of anti-taint methods in a mobile device environment to circumvent this security technique. We have implemented the presented techniques in an Android application, ScrubDroid. We successfully tested our app with the TaintDroid implementations for Android OS versions 2.3 to 4.1.1, both using the emulator and with real devices. Finally, we evaluate the success rate and time to complete of the presented attacks. We conclude that, although taint tracking may be a valuable tool for software developers, it will not effectively protect sensitive data from the black-box code of a motivated attacker applying any of the presented anti-taint tracking methods.
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