Privacy Panel: Usable and Quantifiable Mobile Privacy

摘要: The ever increasing popularity of apps stems from their ability to provide highly customized services the user. flip side is that in order such services, need access very sensitive private information about This leads malicious collect personal user background and exploit it various ways. Studies have shown current app vetting processes which are mainly restricted install time verification mechanisms incapable detecting preventing attacks. We argue missing fundamental aspect here a comprehensive usable mobile privacy solution, one not only protects user's location information, but also other equally data as contacts documents. A solution by average who does understand or care low level technical details. To bridge this gap, we propose metrics quantify low-level accesses terms impact transforms them high-level understandable ratings. design architecture our Privacy Panel represents computed ratings graphical user-friendly format allows define policies based on them. Finally, experimental results given validate scalability proposed solution.