In-app advertising is an essential part to the ecosystem of free mobile applications. On the surface, it creates a win-win situation where app developers can profit from their work, but without charging the users. However, as in the case of web advertising, ad-networks behind in-app advertising employ personalization to improve the effectiveness/profitability of their ad-placement. This need for serving personalized advertisements in turn motivates ad-networks to collect data about users and profile them. As such, “free” apps are only free in monetary terms, but they come with a price of potential privacy concerns. The only question is, how much data are users giving away to pay for the “free apps”? 

In this paper, we study how much of the user's interest and demographic information is known to these major ad networks on mobile platform. We also study if personalized ads can be used by the hosting apps to reconstruct some of the user information collected by the ad network. By collecting more than two hundred real user profiles through surveys, as well as the ads seen by the surveyed users, we found that mobile ads delivered by a major ad network, Google, are personalized based on both users' demographic and interest profiles. In particular, we showed that there is statistically significant correlation between observed ads and the user's profile. We also demonstrated the possibility of learning users' sensitive demographic information such as gender (75% accuracy) and parental status (66% accuracy) through personalized ads because users of different demographics tend to get ads of different contents. These findings illustrate that in-app advertising can leak potentially sensitive user information to any app that hosts personalized ads and ad networks' current protection mechanisms are not sufficient for safe-guarding user's sensitive personal information.