A framework for privacy information protection on Android

Permissions-based security model of Android increasingly shows its vulnerability in protecting users' privacy information. According to the permissions-based security model, an application should have the appropriate permissions before gaining various resources (including data and hardware) in the phone. This model can only restrict an application to access system resources without appropriate permissions, but can not prevent malicious accesses to privacy data after the application having obtained permissions. During the installation of an application, the system will prompt what permissions the application is requesting. Users have no choice but to allow all the requested permissions if they want to use the application. Once an application is successfully installed, the system is unable to control its behavior dynamically, and at this time the application can obtain privacy information and send them out without the acknowledgements of users. Therefore, there is a great security risk of the permissions-based security model. This paper researches on different ways to access users' privacy information and proposes a framework named PriGuard for dynamically protecting users' privacy information based on Binder communication interception technology and feature selection algorithm. Applications customarily call system services remotely by using the Binder mechanism, then access the equipment and obtain information through system services. By redirecting the Binder interface function of Native layer, PriGuard intercepts Binder messages, as a result, intercepting the application's Remote Procedure Call (RPC) for system services, then it can dynamically monitor the application's behaviors that access privacy information. In this paper, we collect many different types of benign Application Package File (APK) samples, and get the Application Programming Interface (API) calls of each sample when it is running. Afterwards we transform these API calls of each sample into feature vectors. Feature selection algorithm is used to generate the optimal feature subset. PriGuard automatically completes the privacy policy configuration on the newly installed software according to the optimal feature subset, and then control the calls on system service of the software using Binder message interception technology, which achieves the purpose of protecting users' privacy information.