An Automated Assessment of Android Clipboards

Wei Wang, Ruoxi Sun, Minhui Xue, D. Ranasinghe
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引用次数: 4

Abstract

Since the new privacy feature in iOS enabling users to acknowledge which app is reading or writing to his or her clipboard through prompting notifications was updated, a plethora of top apps have been reported to frequently access the clipboard without user consent. However, the lack of monitoring and control of Android application's access to the clipboard data leave Android users blind to their potential to leak private information from Android clipboards, raising severe security and privacy concerns. In this preliminary work, we envisage and investigate an approach to (i) dynamically detect clipboard access behaviour, and (ii) determine privacy leaks via static data flow analysis, in which we enhance the results of taint analysis with call graph concatenation to enable leakage source backtracking. Our preliminary results indicate that the proposed method can expose clipboard data leakage as substantiated by our discovery of a popular app, i.e., Sogou Input, directly monitoring and transferring user data in a clipboard to backend servers.
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Android剪贴板的自动评估
由于iOS的新隐私功能更新了,用户可以通过提示通知确认哪个应用正在读取或写入他或她的剪贴板,据报道,大量的热门应用经常未经用户同意访问剪贴板。然而,由于缺乏对Android应用程序访问剪贴板数据的监控和控制,Android用户对从Android剪贴板泄露私人信息的可能性视而不见,从而引发了严重的安全和隐私问题。在这项初步工作中,我们设想并研究了一种方法:(i)动态检测剪贴板访问行为,以及(ii)通过静态数据流分析确定隐私泄漏,其中我们通过调用图连接增强污染分析的结果,以实现泄漏源回溯。我们的初步结果表明,我们所提出的方法可以暴露剪贴板数据泄露,我们发现了一个流行的应用程序,即搜狗Input,直接监控剪贴板中的用户数据并将其传输到后端服务器。
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