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Selective cloaking: Need-to-know for location-based apps

机译:选择性隐蔽:基于位置的应用程序需要知道的

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Currently location privacy settings of mobile operating systems are limited to the option of enabling or disabling the use of location completely or on a per-app basis. When location use is allowed, users always reveal their location in full precision even to apps that do not need it. For instance, weather forecast apps and navigation apps both get the most exact location a device can determine. Up to now, mobile privacy research was focused on the recognition and prevention of disclosure of private data. This includes location data, but does not extend to privacy in use cases where users do want to disclose their location — but not in full detail. However, the increasing adoption of smartphones entails the increasing use of location-based services as well. Users want to use these services, but have privacy concerns. As many location-based services do not require exact locations, user privacy can be increased by only disclosing location in such detail as required for the respective service to function. To enable users to restrict the accuracy of location data that is revealed to apps, we created a location privacy framework that allows per-app location obfuscation. The framework allows easy integration of different obfuscation algorithms into the Android system. We present both on-device obfuscation and service-based obfuscation and evaluate our framework.
机译:当前,移动操作系统的位置隐私设置仅限于完全或基于每个应用启用或禁用位置使用的选项。允许使用位置信息时,用户始终会以最高精度显示其位置,即使是不需要该信息的应用程序也是如此。例如,天气预报应用程序和导航应用程序都可以获取设备可以确定的最精确位置。迄今为止,移动隐私研究一直集中在识别和防止私人数据泄露方面。这包括位置数据,但在用户确实希望公开其位置的用例中,并没有扩展到隐私保护,但并未提供全部详细信息。但是,越来越多的智能手机被采用,这也意味着越来越多地使用基于位置的服务。用户想使用这些服务,但是有隐私方面的顾虑。由于许多基于位置的服务不需要确切的位置,因此可以通过仅公开相应服务运行所需的详细位置来增加用户隐私。为了使用户能够限制显示给应用程序的位置数据的准确性,我们创建了一个位置隐私框架,该框架允许对每个应用程序进行位置混淆。该框架允许将不同的混淆算法轻松集成到Android系统中。我们同时介绍了设备上的混淆和基于服务的混淆,并评估了我们的框架。

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