  Nowadays many people store photos in smartphones. Many of the photos contain
sensitive, private information, such as a photocopy of driver's license and
credit card. An arising privacy concern is with the unauthorized accesses to
such private photos by installed apps. Coarse-grained access control systems
such as the Android permission system offer all-or-nothing access to photos
stored on smartphones, and users are unaware of the exact behavior of installed
apps. Our analysis finds that 82% of the top 200 free apps in a popular Android
app store have complete access to stored photos and network on a user's
smartphone, which indicates possible private photo leakage. In addition, our
user survey reveals that 87.5% of the 112 respondents are not aware that
certain apps can access their photos without informing users, and all the
respondents believe that the stored photos on their smartphones contain
different types of private information. Hence, we propose PhotoSafer, a
content-based, context-aware private photo protection system for Android
phones. PhotoSafer can detect private photos based on photo content with a
well-trained deep convolutional neural network, and control access to photos
based on system status (e.g., screen locked or not) and app-running status
(e.g., app in the background). Evaluations demonstrate that PhotoSafer can
accurately identify private photos in real time. The efficacy and efficiency of
the implemented prototype system show the potential for practical use.
