Sensitive Text Icon Classification for Android Apps
Zhihao Cao · OhioLink ETD Center (Ohio Library and Information Network) · 2017
ZHIHAO CAOAs smartphones have played a very important role in people's daily life, users' privacy and security become a serious concern.Previous research efforts in improving mobile app security mainly focused on the predefined sources of sensitive information managed by smartphone platforms.To the best of our knowledge, text icons, a type of user interface elements that may indicate uses of the users' sensitive information, have been largely neglected.In this thesis, we proposed an approach to automatically identify text icons in the UIs of smartphone apps, and classify them into predefined categories of sensitive information.In particular, we developed an algorithm DroidIcon based on OCR (Optical Character Recognition) to determine whether the texts contained in text icons indicate uses of sensitive information.To evaluate the effectiveness of DroidIcon, we apply the algorithm to 707 text icons collected from 2000 popular Android apps.The algorithm achieves an accuracy of 90.52%, a precision of 91.28% and a recall of 88.25% for classifying text icons into pre-defined categories of sensitive information.