Identifying and Analyzing the Privacy of Apps for Kids
Minxing Liu, Haoyu Wang, Yao Guo, and Jason Hong
Workshop on Mobile Computing Systems and Applications (HotMobile)
February 2016
One aspect of privacy that has not been well explored is privacy for children. We present the design and evaluation of a machine learning model for predicting whether a mobile app is designed for children, which is an important step in helping to enforce the Children's Online Privacy Protection Act (COPPA). We evaluated our model on 1,728 apps from Google Play and achieved 95% accuracy. We also applied our model on a set of nearly 1 million free apps from Google Play, and identified almost 68,000 apps for kids. We then conducted a privacy analysis of the usage of third-party libraries for each app, which can help us understand some of the app's privacy-related behaviors. We believe this list can serve as a good start point for further fi ne-grained privacy analysis on mobile apps for children.
