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SieveDroid: Intercepting Undesirable Private-Data Transmissions in Android Applications

机译:secieRroid:拦截Android应用程序中的不良私有数据传输

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摘要

Android applications may abuse their permissions on private data, leaking the user's privacy out of the mobile device via data transmissions. A straightforward way to deal with this problem is to restrict the application permissions. However, the restriction not only prevents the undesirable operations fromleaking privacy but also prohibits the desirable operations from utilizing private data. Ourgoal is to get both of the points: ensuring the user's privacy by preventing undesirable private-data transmissions and enduring no degradation on the desirable application functionalities. We propose SieveDroid, a fine-grained runtime privacy control framework. SieveDroid addresses two key challenges of intercepting the undesirable private-data transmissions: revealing how private-data transmissions occur to end-users and setting privacy control rules which intercept the undesirable private-data transmissions at runtime without interfering with desirable ones. We evaluate SieveDroid by using Android malware samples and real applications from the Android market. The results demonstrate that SieveDroid reveals the undesirable operations precisely and concisely and it can effectively intercept the undesirable data transmissions. Besides, desirable functionalities in 98% of the tested applications are not affected.
机译:Android应用程序可能会滥用其对私有数据的权限,通过数据传输将用户的隐私泄漏出来。处理此问题的直接方式是限制应用程序权限。但是,限制不仅可以防止不良操作释放隐私,而且还禁止使用私有数据的理想操作。 Ougoal是为了获得两个要点:通过防止不希望的私有数据传输并持久地没有对所需应用功能的劣化来确保用户的隐私。我们提出Sectionroid,一个细粒度的运行时间隐私控制框架。 SectionroId解决了拦截不良私有数据传输的两个关键挑战:揭示私有数据传输如何发生在最终用户和设置隐私控制规则,该规则拦截运行时在运行时拦截不期望的私有数据传输,而不会干扰所需的私有数据传输。我们通过使用Android Mallware样本和来自Android Market的真实应用程序来评估SectioRID。结果表明,分析器精确且简洁地揭示了不良操作,并且它可以有效地拦截不期望的数据传输。此外,98%的测试应用中的理想功能不受影响。

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