Demystifying Hidden Privacy Settings in Mobile Apps

Yi Chen, Mingming Zha, Nan Zhang, Dandan Xu, Qianqian Zhao, Xuan Feng, Kan Yuan, Fnu Suya, Yuan Tian, Kai Chen, Xiaofeng Wang, Wei Zou
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引用次数: 21

Abstract

Mobile apps include privacy settings that allow their users to configure how their data should be shared. These settings, however, are often hard to locate and hard to understand by the users, even in popular apps, such as Facebook. More seriously, they are often set to share user data by default, exposing her privacy without proper consent. In this paper, we report the first systematic study on the problem, which is made possible through an in-depth analysis of user perception of the privacy settings. More specifically, we first conduct two user studies (involving nearly one thousand users) to understand privacy settings from the user’s perspective, and identify these hard-to-find settings. Then we select 14 features that uniquely characterize such hidden privacy settings and utilize a novel technique called semantics- based UI tracing to extract them from a given app. On top of these features, a classifier is trained to automatically discover the hidden privacy settings, which together with other innovations, has been implemented into a tool called Hound. Over our labeled data set, the tool achieves an accuracy of 93.54%. Further running it on 100,000 latest apps from both Google Play and third-party markets, we find that over a third (36.29%) of the privacy settings identified from these apps are “hidden”. Looking into these settings, we observe that they become hard to discover and hard to understand primarily due to the problematic categorization on the apps’ user interfaces and/or confusing descriptions. Further importantly, though more privacy options have been offered to the user over time, also discovered is the persistence of their usability issue, which becomes even more serious, e.g., originally easy-to-find settings now harder to locate. And among all such hidden privacy settings, 82.16% are set to leak user privacy by default. We provide suggestions for improving the usability of these privacy settings at the end of our study.
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揭秘手机应用中隐藏的隐私设置
移动应用程序包括隐私设置,允许用户配置他们的数据应该如何共享。然而,这些设置通常很难定位,用户也很难理解,即使在Facebook等流行应用程序中也是如此。更严重的是,它们通常默认设置为共享用户数据,在未经适当同意的情况下暴露了用户的隐私。在本文中,我们报告了对该问题的第一个系统研究,这是通过深入分析用户对隐私设置的感知而实现的。更具体地说,我们首先进行了两次用户研究(涉及近千名用户),从用户的角度了解隐私设置,并识别这些难以找到的设置。然后,我们选择了14个独特表征这种隐藏隐私设置的特征,并利用一种称为基于语义的UI跟踪的新技术从给定的应用程序中提取它们。在这些特征之上,训练分类器来自动发现隐藏的隐私设置,这与其他创新一起被实现到一个名为Hound的工具中。在我们的标记数据集上,该工具达到了93.54%的准确率。进一步在Google Play和第三方市场的10万款最新应用上运行,我们发现超过三分之一(36.29%)的隐私设置是“隐藏的”。通过观察这些设置,我们发现它们变得难以发现和理解,主要是由于应用程序用户界面上有问题的分类和/或令人困惑的描述。更重要的是,尽管随着时间的推移,用户可以选择更多的隐私选项,但我们也发现,它们的可用性问题持续存在,变得更加严重,例如,原本容易找到的设置现在更难找到。而在这些隐藏隐私设置中,82.16%默认设置为泄露用户隐私。在研究结束时,我们提供了改进这些隐私设置可用性的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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