The Price of Free: Privacy Leakage in Personalized Mobile In-Apps Ads

In-app advertising is an essential part of the ecosystem of free mobile applications. On the surface, this creates a win-win situation where app developers can profit from their work 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; they come with the price of potential privacy concerns. The question is, how much data are users giving away to pay for "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 the mobile platform. We also study whether 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 a statistically significant correlation between observed ads and the user's profile. Since users of different demographics tend to get ads of different contents, we also demonstrated the likelihood of learning users' sensitive demographic information such as gender (75% accuracy) and parental status (66% accuracy) through personalized ads. 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 users' sensitive personal information.