The transparency and privacy behavior of mobile browsers has remained widely unexplored by the research community. In fact, as opposed to regular Android apps, mobile browsers may present contradicting privacy behaviors. On the one end, they can have access to (and can expose) a unique combination of sensitive user data, from users' browsing history to permission-protected personally identifiable information (PII) such as unique identifiers and geolocation. However, on the other end, they also are in a unique position to protect users' privacy by limiting data sharing with other parties by implementing ad-blocking features. In this paper, we perform a comparative and empirical analysis on how hundreds of Android web browsers protect or expose user data during browsing sessions. To this end, we collect the largest dataset of Android browsers to date, from the Google Play Store and four Chinese app stores. Then, we developed a novel analysis pipeline that combines static and dynamic analysis methods to find a wide range of privacy-enhancing (e.g., ad-blocking) and privacy-harming behaviors (e.g., sending browsing histories to third parties, not validating TLS certificates, and exposing PII -- including non-resettable identifiers -- to third parties) across browsers. We find that various popular apps on both Google Play and Chinese stores have these privacy-harming behaviors, including apps that claim to be privacy-enhancing in their descriptions. Overall, our study not only provides new insights into important yet overlooked considerations for browsers' adoption and transparency, but also that automatic app analysis systems (e.g., sandboxes) need context-specific analysis to reveal such privacy behaviors.
翻译:移动浏览器的透明度和隐私行为一直没有被研究界广泛探索。 事实上, 与常规安道普相比, 移动浏览器可能会显示与隐私行为相矛盾的隐私行为。 一方面, 他们可以访问( 并能够披露)敏感用户数据的独特组合, 从用户浏览历史到允许保护个人可识别信息( PII), 如独特的标识符和地理定位。 然而, 在另一方面, 它们也处于保护用户隐私的独特地位, 通过实施封存功能限制与其他缔约方共享数据。 在本文中, 我们进行对比性和经验分析, 了解数百个安道网络浏览器如何在浏览会话中保护或披露用户数据。 为此, 我们收集了迄今为止最大的安道浏览器数据集, 从Google Play Store 和四家中国应用程序商店。 然后, 我们开发了一个新分析管道, 将静态和动态分析方法组合起来, 以找到广泛的隐私强化( 例如, 封存) 以及隐私行为( ) 而非伤害行为( 例如, 包括: 将浏览器浏览器分析, 包括各种智能浏览器, 向这些交易的各方, 等, 向这些交易中, 包括: