On Usable Location Privacy for Android with Crowd-Recommendations
The boom of smart devices with location capabilities has also led to a boom of apps that use location data for many different purposes. While there are of course apps that require users’ precise locations, such as navigation apps, many apps would work equally well with less precision. Currently, apps that request location information are granted access to location data with maximum precision or not at all. In this work we present a location obfuscation approach for Android devices, which focuses on the usability aspects. Based on results of focus group discussions (n,=,19) we designed and implemented a solution that can be used by even unskilled users. When an app requests for location data the first time, the user configures accuracy of location data that is to be revealed to the app by selecting one of five precision levels. Unskilled users are supported by crowd-based recommendations.
Keywordsmobile usable security and privacy location crowd-sourcing
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